SK hynix memory solutions America Inc.
San Jose, California
Job Description Job Description About the Company: At SK Hynix Memory Solution, we're at the forefront of semiconductor innovation, developing advanced memory solutions that power everything from smartphones to data centers. As a global leader in DRAM and NAND flash technologies, we drive the evolution of advancing mobile technology, empowering cloud computing, and pioneering future technologies. Our cutting-edge memory technologies are essential in today's most advanced electronic devices and IT infrastructure, enabling enhanced performance and user experiences across the digital landscape. We're looking for innovative minds to join our mission of shaping the future of technology. At SK Hynix Memory, you'll be part of a team that's pioneering breakthrough memory solutions while maintaining a strong commitment to sustainability. We're not just adapting to technological change - we're driving it, with significant investments in artificial intelligence, machine learning, and eco-friendly solutions and operational practices. As we continue to expand our market presence and push the boundaries of what's possible in semiconductor technology, we invite you to be part of our journey to creating the next generation of memory solutions that will define the future of computing. About the Team SK hynix memory solutions America Inc. (SKHMS America), a subsidiary of SK hynix NAND Product Solutions (D.B.A Solidigm), provides industry-leading controller hardware, advanced flash management systems, and firmware for NAND and post 2D-NAND based storage solutions spanning Enterprise, Client and Mobile market segments. We are part of the world's top tier semiconductor supplier, SK hynix, offering Dynamic Random Access Memory chips (DRAM), Flash memory chips (NAND Flash) and CMOS Image Sensor (CIS) for a wide range of distinguished customers globally. Description We are looking for a driven, team-oriented Senior Signal Integrity Engineer to develop next generation Solid State Drive (SSD) products. This position requires experience in hardware design and signal and power integrity design. A successful candidate will have a good knowledge of state of the art memory device technologies and interfaces such as PCIe Gen 4, 5 and 6, DDR4/5, ONFI NAND and implementation techniques required for high-speed interfaces. This candidate will need to have a good working knowledge of simulation tools, schematic capture tools and lab equipment (scopes, analyzers, etc.). Expertise in design for optimum signal and power integrity as well as hands-on lab measurements experience is a must. Responsibilities Mentoring of engineers. Provide SI/PI expertise for SSD controller package (SoC) substrate design and SSD PCB design. Participate in the design of SSD products which includes: design guidelines, reviewing designs, validation of designs and final reports of work designs. Support PCB back-end process: defining stack-up and HDI via technologies, part placement, setting routing constraints and reviews. Interface with cross functional teams to ensure the design meets all system level requirements through verification/validation in the lab. Work closely with SoC, FW, package, and circuit design engineers. Documentation and communication to design, product and executive teams. Debug and root cause analysis at all product development stages, as well as customer escalations. Minimum Qualifications BS in Electrical Engineering required; MS in Electrical Engineering is a plus. 3-8+ years of relevant working experience. High-speed SSD board designs, pre layout simulation, post layout simulation and design layout guide generation for PCIe Gen4/5/6, DDR4/5, LPDDR4/4x, NVIO and PDN. Strong fundamentals in 3D/2D EM simulation tools and transmission line theory. Required experience of EM field solvers, time and frequency domain simulation tools like Sigrity, Allegro, ADS, HFSS, SIWAVE, and HSPICE. Simulation followed by measurement correlation using Oscilloscope, VNA and TDR equipment. Excellent understanding of PCB design fundamentals: single end and differential signaling, cross talk (near end and far end), signal loss and impedance control. Excellent written and verbal communication. Preferred Qualifications Technical leader experience. Familiar with generating and interpreting data & eye diagrams at PCIe GENx speeds: NRZ, PAM3, PAM4, PAMx. High Frequency pcb low loss board material experience. Experience with flex circuit design for high speed signaling. Familiarity with PCIe operation and DRAM operation for optimizing driver and receiver equalization schemes. Knowledge of IBIS and ability to take common simulation outputs such as S-parameters from various components and determine at the system level that PRD requirements are met. Optimizing PDN and extracting PDN for PSIJ Analysis. Familiar with PCISIG, JEDEC and ONFI specifications and compliance. COMPENSATION : $110,000/yr - $175,000/yr REGARDING COMPENSATION : SK hynix memory solutions America Inc. offers you the opportunity to apply your skills to exciting projects while working with innovative teams. Our compensation package is complimented by a generous benefits package including medical, dental, vision, life insurance and a company 401(k) match, as well as cafeteria, onsite gym and much more. If you are motivated by technical challenges, we offer a collaborative work environment that encourages career growth. The salary offered to a selected candidate will be tailored based on several factors, including the location, job grade, relevant knowledge, skills, and experience. We also take into account the internal equity among our current team members to ensure fairness and competitiveness
10/26/2026
Full time
Job Description Job Description About the Company: At SK Hynix Memory Solution, we're at the forefront of semiconductor innovation, developing advanced memory solutions that power everything from smartphones to data centers. As a global leader in DRAM and NAND flash technologies, we drive the evolution of advancing mobile technology, empowering cloud computing, and pioneering future technologies. Our cutting-edge memory technologies are essential in today's most advanced electronic devices and IT infrastructure, enabling enhanced performance and user experiences across the digital landscape. We're looking for innovative minds to join our mission of shaping the future of technology. At SK Hynix Memory, you'll be part of a team that's pioneering breakthrough memory solutions while maintaining a strong commitment to sustainability. We're not just adapting to technological change - we're driving it, with significant investments in artificial intelligence, machine learning, and eco-friendly solutions and operational practices. As we continue to expand our market presence and push the boundaries of what's possible in semiconductor technology, we invite you to be part of our journey to creating the next generation of memory solutions that will define the future of computing. About the Team SK hynix memory solutions America Inc. (SKHMS America), a subsidiary of SK hynix NAND Product Solutions (D.B.A Solidigm), provides industry-leading controller hardware, advanced flash management systems, and firmware for NAND and post 2D-NAND based storage solutions spanning Enterprise, Client and Mobile market segments. We are part of the world's top tier semiconductor supplier, SK hynix, offering Dynamic Random Access Memory chips (DRAM), Flash memory chips (NAND Flash) and CMOS Image Sensor (CIS) for a wide range of distinguished customers globally. Description We are looking for a driven, team-oriented Senior Signal Integrity Engineer to develop next generation Solid State Drive (SSD) products. This position requires experience in hardware design and signal and power integrity design. A successful candidate will have a good knowledge of state of the art memory device technologies and interfaces such as PCIe Gen 4, 5 and 6, DDR4/5, ONFI NAND and implementation techniques required for high-speed interfaces. This candidate will need to have a good working knowledge of simulation tools, schematic capture tools and lab equipment (scopes, analyzers, etc.). Expertise in design for optimum signal and power integrity as well as hands-on lab measurements experience is a must. Responsibilities Mentoring of engineers. Provide SI/PI expertise for SSD controller package (SoC) substrate design and SSD PCB design. Participate in the design of SSD products which includes: design guidelines, reviewing designs, validation of designs and final reports of work designs. Support PCB back-end process: defining stack-up and HDI via technologies, part placement, setting routing constraints and reviews. Interface with cross functional teams to ensure the design meets all system level requirements through verification/validation in the lab. Work closely with SoC, FW, package, and circuit design engineers. Documentation and communication to design, product and executive teams. Debug and root cause analysis at all product development stages, as well as customer escalations. Minimum Qualifications BS in Electrical Engineering required; MS in Electrical Engineering is a plus. 3-8+ years of relevant working experience. High-speed SSD board designs, pre layout simulation, post layout simulation and design layout guide generation for PCIe Gen4/5/6, DDR4/5, LPDDR4/4x, NVIO and PDN. Strong fundamentals in 3D/2D EM simulation tools and transmission line theory. Required experience of EM field solvers, time and frequency domain simulation tools like Sigrity, Allegro, ADS, HFSS, SIWAVE, and HSPICE. Simulation followed by measurement correlation using Oscilloscope, VNA and TDR equipment. Excellent understanding of PCB design fundamentals: single end and differential signaling, cross talk (near end and far end), signal loss and impedance control. Excellent written and verbal communication. Preferred Qualifications Technical leader experience. Familiar with generating and interpreting data & eye diagrams at PCIe GENx speeds: NRZ, PAM3, PAM4, PAMx. High Frequency pcb low loss board material experience. Experience with flex circuit design for high speed signaling. Familiarity with PCIe operation and DRAM operation for optimizing driver and receiver equalization schemes. Knowledge of IBIS and ability to take common simulation outputs such as S-parameters from various components and determine at the system level that PRD requirements are met. Optimizing PDN and extracting PDN for PSIJ Analysis. Familiar with PCISIG, JEDEC and ONFI specifications and compliance. COMPENSATION : $110,000/yr - $175,000/yr REGARDING COMPENSATION : SK hynix memory solutions America Inc. offers you the opportunity to apply your skills to exciting projects while working with innovative teams. Our compensation package is complimented by a generous benefits package including medical, dental, vision, life insurance and a company 401(k) match, as well as cafeteria, onsite gym and much more. If you are motivated by technical challenges, we offer a collaborative work environment that encourages career growth. The salary offered to a selected candidate will be tailored based on several factors, including the location, job grade, relevant knowledge, skills, and experience. We also take into account the internal equity among our current team members to ensure fairness and competitiveness
SK hynix memory solutions America Inc.
San Jose, California
Job Description Job Description About the Company: At SK Hynix Memory Solution, we're at the forefront of semiconductor innovation, developing advanced memory solutions that power everything from smartphones to data centers. As a global leader in DRAM and NAND flash technologies, we drive the evolution of advancing mobile technology, empowering cloud computing, and pioneering future technologies. Our cutting-edge memory technologies are essential in today's most advanced electronic devices and IT infrastructure, enabling enhanced performance and user experiences across the digital landscape. We're looking for innovative minds to join our mission of shaping the future of technology. At SK Hynix Memory, you'll be part of a team that's pioneering breakthrough memory solutions while maintaining a strong commitment to sustainability. We're not just adapting to technological change - we're driving it, with significant investments in artificial intelligence, machine learning, and eco-friendly solutions and operational practices. As we continue to expand our market presence and push the boundaries of what's possible in semiconductor technology, we invite you to be part of our journey to creating the next generation of memory solutions that will define the future of computing. About the Team You will join the System on Chip (SoC) Design Team at SK Hynix memory solutions America, a group dedicated to delivering best-in-class controllers for high-performance SSDs. This team spans the full design cycle-from micro-architecture and RTL design to timing closure and tapeout readiness-enabling next-generation enterprise and AI data center storage solutions. As a Staff Engineer, you will own critical High speed interface IP, drive methodology improvements (such as AI-assisted design flows), and mentor engineers to ensure first-pass silicon success. Responsibilities Design and verification of the high speed interface for next generation storage subsystem for NVME or Chiplet. Drive team efforts with multi-function teams from RTL development through silicon bring-up. Minimum Qualifications 3 - 7 years of experience in ASIC design. Experience debugging RTL using Verdi/VCS and automating tasks via Python or Perl. Experience in SystemVerilog/Verilog for RTL development and microarchitecture definition. Experience with Clock Domain Crossing (CDC), timing closure, synthesis flows or Gate Level Simulation(GLS). Preferred Qualifications Experience in PCle(Gen4/5/6) architecture in TLP/FLIT pipelines, flow control, ordering rules, and performance tuning. Proven experience with Link training, power state(L0/L0P/L1/L2), error handling (AER). Experience with cross-functional leadership, driving efforts with software/system teams from RTL development through silicon bring-up. Good plus to have experience in AI Assist design flow. Education Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. REGARDING COMPENSATION: SK hynix memory solutions America Inc. offers you the opportunity to apply your skills to exciting projects while working with innovative teams. Our compensation package is complimented by a generous benefits package including medical, dental, vision, life insurance and a company 401(k) match, as well as cafeteria, onsite gym and much more. If you are motivated by technical challenges, we offer a collaborative work environment that encourages career growth. The salary offered to a selected candidate will be tailored based on several factors, including the location, job grade, relevant knowledge, skills, and experience. We also take into account the internal equity among our current team members to ensure fairness and competitiveness.
10/26/2026
Full time
Job Description Job Description About the Company: At SK Hynix Memory Solution, we're at the forefront of semiconductor innovation, developing advanced memory solutions that power everything from smartphones to data centers. As a global leader in DRAM and NAND flash technologies, we drive the evolution of advancing mobile technology, empowering cloud computing, and pioneering future technologies. Our cutting-edge memory technologies are essential in today's most advanced electronic devices and IT infrastructure, enabling enhanced performance and user experiences across the digital landscape. We're looking for innovative minds to join our mission of shaping the future of technology. At SK Hynix Memory, you'll be part of a team that's pioneering breakthrough memory solutions while maintaining a strong commitment to sustainability. We're not just adapting to technological change - we're driving it, with significant investments in artificial intelligence, machine learning, and eco-friendly solutions and operational practices. As we continue to expand our market presence and push the boundaries of what's possible in semiconductor technology, we invite you to be part of our journey to creating the next generation of memory solutions that will define the future of computing. About the Team You will join the System on Chip (SoC) Design Team at SK Hynix memory solutions America, a group dedicated to delivering best-in-class controllers for high-performance SSDs. This team spans the full design cycle-from micro-architecture and RTL design to timing closure and tapeout readiness-enabling next-generation enterprise and AI data center storage solutions. As a Staff Engineer, you will own critical High speed interface IP, drive methodology improvements (such as AI-assisted design flows), and mentor engineers to ensure first-pass silicon success. Responsibilities Design and verification of the high speed interface for next generation storage subsystem for NVME or Chiplet. Drive team efforts with multi-function teams from RTL development through silicon bring-up. Minimum Qualifications 3 - 7 years of experience in ASIC design. Experience debugging RTL using Verdi/VCS and automating tasks via Python or Perl. Experience in SystemVerilog/Verilog for RTL development and microarchitecture definition. Experience with Clock Domain Crossing (CDC), timing closure, synthesis flows or Gate Level Simulation(GLS). Preferred Qualifications Experience in PCle(Gen4/5/6) architecture in TLP/FLIT pipelines, flow control, ordering rules, and performance tuning. Proven experience with Link training, power state(L0/L0P/L1/L2), error handling (AER). Experience with cross-functional leadership, driving efforts with software/system teams from RTL development through silicon bring-up. Good plus to have experience in AI Assist design flow. Education Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. REGARDING COMPENSATION: SK hynix memory solutions America Inc. offers you the opportunity to apply your skills to exciting projects while working with innovative teams. Our compensation package is complimented by a generous benefits package including medical, dental, vision, life insurance and a company 401(k) match, as well as cafeteria, onsite gym and much more. If you are motivated by technical challenges, we offer a collaborative work environment that encourages career growth. The salary offered to a selected candidate will be tailored based on several factors, including the location, job grade, relevant knowledge, skills, and experience. We also take into account the internal equity among our current team members to ensure fairness and competitiveness.
Machine Learning Engineer 4 (Manager, IC) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/26/2026
Full time
Machine Learning Engineer 4 (Manager, IC) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 1 year of people leadership experience Preferred Qualifications: 3 years of experience managing and leading an engineering team 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance Track record mentoring engineers/scientists to productize prototypes and meet production SLOs Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
10/26/2026
Full time
Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 1 year of people leadership experience Preferred Qualifications: 3 years of experience managing and leading an engineering team 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance Track record mentoring engineers/scientists to productize prototypes and meet production SLOs Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 1 year of people leadership experience Preferred Qualifications: 3 years of experience managing and leading an engineering team 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance Track record mentoring engineers/scientists to productize prototypes and meet production SLOs Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
10/26/2026
Full time
Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 1 year of people leadership experience Preferred Qualifications: 3 years of experience managing and leading an engineering team 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance Track record mentoring engineers/scientists to productize prototypes and meet production SLOs Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
Machine Learning Engineer 4 (Manager, IC) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/26/2026
Full time
Machine Learning Engineer 4 (Manager, IC) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/26/2026
Full time
Machine Learning Engineer 4 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Machine Learning Experiences (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/26/2026
Full time
Machine Learning Engineer 4 - Machine Learning Experiences (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/26/2026
Full time
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/26/2026
Full time
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/26/2026
Full time
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Machine Learning Experiences (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/26/2026
Full time
Machine Learning Engineer 4 - Machine Learning Experiences (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Machine Learning Experiences (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/26/2026
Full time
Machine Learning Engineer 4 - Machine Learning Experiences (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. About The Team We're building the shared platform and AI capabilities that enable CoverMyMeds to deliver modern, role-based digital products quickly, securely, and at scale. Our team creates the foundational services, experiences, and technology patterns that power multiple products across the organization, accelerating innovation while ensuring reliability, compliance, and reusability. What You'll Do Digital Product & Experience Own the vision, roadmap, and backlog for role-based digital workspaces that unify workflows, communications, data, and AI-powered assistance. Lead user discovery with internal and external stakeholders to identify pain points and translate insights into prioritized product investments. Define and execute phased delivery strategies through MVPs, pilots, and scalable release plans that maximize user value and platform reuse. Platform & API Products Define requirements for shared platform services, including API management, backend-for-frontend (BFF) services, event-driven integrations, and identity and access management. Manage APIs and platform capabilities as products, establishing clear service definitions, documentation, adoption strategies, and performance expectations. Guide modernization efforts that enable legacy and cloud-native systems to operate together while minimizing disruption to business operations. Drive requirements for reusable communication services such as SMS, email, fax, voice, and chat capabilities. AI Product Capabilities Shape and deliver AI-driven solutions including conversational AI, virtual agents, knowledge search, question-answering experiences, document AI, and generative AI assistants. Define and measure success metrics such as containment rates, accuracy, operational efficiency, time savings, and business impact. Partner with engineering, data science, security, and compliance teams to ensure AI solutions are governed, explainable, and appropriate for regulated environments. Data Foundations Collaborate with data teams to define data models, pipelines, and trusted data sources that support products, analytics, and AI initiatives. Ensure privacy, security, and data-governance requirements are incorporated throughout the product lifecycle. Ways of Working Operate within a SAFe environment by authoring epics, features, and user stories while actively participating in PI Planning and dependency management. Represent product priorities in architecture and governance reviews, translating technical decisions into business outcomes. Champion AI-first ways of working by leveraging AI tools to improve research, planning, documentation, and product delivery. Skills You'll Need 5+ years of product management experience delivering digital products, platform products, APIs, or internal tooling solutions. Strong understanding of modern architecture patterns, including APIs, API gateways, microservices, BFF architectures, event-driven systems, cloud platforms, and identity/access management. Experience launching and managing AI or machine learning capabilities such as conversational AI, generative AI assistants, document processing, or intelligent automation solutions. Proven success leading legacy modernization initiatives through phased migration strategies. Strong product discovery, roadmap prioritization, stakeholder management, and agile delivery experience. Ability to communicate effectively with both executive business stakeholders and technical teams. Demonstrated use of data and analytics to inform decisions and measure outcomes. Experience leveraging AI tools to improve productivity and product management practices. Preferred Skills Experience in healthcare, pharmacy, or another highly regulated industry. Knowledge of HIPAA, privacy regulations, security controls, and data-governance requirements. Experience with telephony, contact center technologies, or omnichannel communication platforms. Familiarity with data platforms, analytics ecosystems, and modern data engineering solutions such as Databricks. Experience delivering enterprise-scale platform products supporting multiple teams and business functions. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $94,500 - $157,500 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!
10/25/2026
Full time
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. About The Team We're building the shared platform and AI capabilities that enable CoverMyMeds to deliver modern, role-based digital products quickly, securely, and at scale. Our team creates the foundational services, experiences, and technology patterns that power multiple products across the organization, accelerating innovation while ensuring reliability, compliance, and reusability. What You'll Do Digital Product & Experience Own the vision, roadmap, and backlog for role-based digital workspaces that unify workflows, communications, data, and AI-powered assistance. Lead user discovery with internal and external stakeholders to identify pain points and translate insights into prioritized product investments. Define and execute phased delivery strategies through MVPs, pilots, and scalable release plans that maximize user value and platform reuse. Platform & API Products Define requirements for shared platform services, including API management, backend-for-frontend (BFF) services, event-driven integrations, and identity and access management. Manage APIs and platform capabilities as products, establishing clear service definitions, documentation, adoption strategies, and performance expectations. Guide modernization efforts that enable legacy and cloud-native systems to operate together while minimizing disruption to business operations. Drive requirements for reusable communication services such as SMS, email, fax, voice, and chat capabilities. AI Product Capabilities Shape and deliver AI-driven solutions including conversational AI, virtual agents, knowledge search, question-answering experiences, document AI, and generative AI assistants. Define and measure success metrics such as containment rates, accuracy, operational efficiency, time savings, and business impact. Partner with engineering, data science, security, and compliance teams to ensure AI solutions are governed, explainable, and appropriate for regulated environments. Data Foundations Collaborate with data teams to define data models, pipelines, and trusted data sources that support products, analytics, and AI initiatives. Ensure privacy, security, and data-governance requirements are incorporated throughout the product lifecycle. Ways of Working Operate within a SAFe environment by authoring epics, features, and user stories while actively participating in PI Planning and dependency management. Represent product priorities in architecture and governance reviews, translating technical decisions into business outcomes. Champion AI-first ways of working by leveraging AI tools to improve research, planning, documentation, and product delivery. Skills You'll Need 5+ years of product management experience delivering digital products, platform products, APIs, or internal tooling solutions. Strong understanding of modern architecture patterns, including APIs, API gateways, microservices, BFF architectures, event-driven systems, cloud platforms, and identity/access management. Experience launching and managing AI or machine learning capabilities such as conversational AI, generative AI assistants, document processing, or intelligent automation solutions. Proven success leading legacy modernization initiatives through phased migration strategies. Strong product discovery, roadmap prioritization, stakeholder management, and agile delivery experience. Ability to communicate effectively with both executive business stakeholders and technical teams. Demonstrated use of data and analytics to inform decisions and measure outcomes. Experience leveraging AI tools to improve productivity and product management practices. Preferred Skills Experience in healthcare, pharmacy, or another highly regulated industry. Knowledge of HIPAA, privacy regulations, security controls, and data-governance requirements. Experience with telephony, contact center technologies, or omnichannel communication platforms. Familiarity with data platforms, analytics ecosystems, and modern data engineering solutions such as Databricks. Experience delivering enterprise-scale platform products supporting multiple teams and business functions. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $94,500 - $157,500 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!
Job Description About Quantiphi: Quantiphi is an award-winning, AI-First global digital engineering company that helps the world's leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies-we solve the problems that matter most to our clients. Since our founding in 2013, Quantiphi has built a proven track record of turning complex challenges into meaningful outcomes across industries. Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation. . We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including: 21 Google Cloud Partner of the Year awards in the past 10 years 3 AWS AI/ML Partner of the Year awards 3 NVIDIA Partner of the Year awards 3 Snowflake Partner of the Year awards Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst firms Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators. We are also proud to be certified as a Great Place to Work-reflecting our commitment to our people and our culture. For more details, visit: Website or LinkedIn Page Role: Senior Engagement Manager Employment type: Full Time Experience: 8+ years Location : Remote (USA) Description: We are looking for a strong EM lead with people management experience to lead a team of business analysts and engineers focused on building and driving solutions and insights to drive business efficiency and customer experience. The ideal candidate will have strong project management, leadership and cross-group collaboration skills. What You Will Do: As an Senior Engagement Manager, you'll lead the delivery management of multi-functional medium/large scale AWS programs, covering project planning, delivery assurance and verification, tracking and reporting, and risk/mitigation planning. Take accountability for our customers to ensure the program(s) realizes financial benefits and transformational outcomes, constantly identify and develop new business opportunities. Work with engineering leads in strategizing and executing multi-year roadmap on portfolio of products, applications, and services. Ensure quality execution and proactively identify potential customer issues and resolve them with speed and efficiency, to drive satisfaction, outcomes, and deliver positive customer partner experience. Coordinate, measure, monitor and communicate on program(s) health. Actively contribute to org-wide strategies, in defining and implementing those along with contributing to team's roadmap and portfolio of services in alignment to the wider organization. Maintain a relentless focus across the team on continuous improvement, planning and implementing changes to process, service and technology to transform how the team operates. Build a collaborative environment - coach/mentor team members. Recruit, motivate and develop highly skilled staffs that focuses on service delivery of key performance metrics as per the client contract. Basic Qualifications: Minimum 8 yrs of experience in delivering digital transformation projects to global clients. Experience in program management, client service, and/or management consulting. Knowledge of leading teams on projects using agile methodology and frameworks like scrum, kanban or XP, etc. Strong verbal and written communication skills with technical and business leaders at all levels within large enterprises. Aptitude in business analysis and leveraging quantitative analysis techniques for decision making. Ability to work with minimal supervision in a dynamic and time sensitive work environment. Knowledge and willingness to learn and apply emerging trends in business research, data science, artificial intelligence, machine learning, and cloud computing - AWS exposure is a value addition. Team management experience is a must. What is in it for you: Join one of the world's fastest-growing AI-first digital engineering companies and make a real impact at scale. Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges. Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents. Stay ahead of the curve by gaining hands-on experience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling.
10/25/2026
Full time
Job Description About Quantiphi: Quantiphi is an award-winning, AI-First global digital engineering company that helps the world's leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies-we solve the problems that matter most to our clients. Since our founding in 2013, Quantiphi has built a proven track record of turning complex challenges into meaningful outcomes across industries. Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation. . We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including: 21 Google Cloud Partner of the Year awards in the past 10 years 3 AWS AI/ML Partner of the Year awards 3 NVIDIA Partner of the Year awards 3 Snowflake Partner of the Year awards Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst firms Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators. We are also proud to be certified as a Great Place to Work-reflecting our commitment to our people and our culture. For more details, visit: Website or LinkedIn Page Role: Senior Engagement Manager Employment type: Full Time Experience: 8+ years Location : Remote (USA) Description: We are looking for a strong EM lead with people management experience to lead a team of business analysts and engineers focused on building and driving solutions and insights to drive business efficiency and customer experience. The ideal candidate will have strong project management, leadership and cross-group collaboration skills. What You Will Do: As an Senior Engagement Manager, you'll lead the delivery management of multi-functional medium/large scale AWS programs, covering project planning, delivery assurance and verification, tracking and reporting, and risk/mitigation planning. Take accountability for our customers to ensure the program(s) realizes financial benefits and transformational outcomes, constantly identify and develop new business opportunities. Work with engineering leads in strategizing and executing multi-year roadmap on portfolio of products, applications, and services. Ensure quality execution and proactively identify potential customer issues and resolve them with speed and efficiency, to drive satisfaction, outcomes, and deliver positive customer partner experience. Coordinate, measure, monitor and communicate on program(s) health. Actively contribute to org-wide strategies, in defining and implementing those along with contributing to team's roadmap and portfolio of services in alignment to the wider organization. Maintain a relentless focus across the team on continuous improvement, planning and implementing changes to process, service and technology to transform how the team operates. Build a collaborative environment - coach/mentor team members. Recruit, motivate and develop highly skilled staffs that focuses on service delivery of key performance metrics as per the client contract. Basic Qualifications: Minimum 8 yrs of experience in delivering digital transformation projects to global clients. Experience in program management, client service, and/or management consulting. Knowledge of leading teams on projects using agile methodology and frameworks like scrum, kanban or XP, etc. Strong verbal and written communication skills with technical and business leaders at all levels within large enterprises. Aptitude in business analysis and leveraging quantitative analysis techniques for decision making. Ability to work with minimal supervision in a dynamic and time sensitive work environment. Knowledge and willingness to learn and apply emerging trends in business research, data science, artificial intelligence, machine learning, and cloud computing - AWS exposure is a value addition. Team management experience is a must. What is in it for you: Join one of the world's fastest-growing AI-first digital engineering companies and make a real impact at scale. Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges. Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents. Stay ahead of the curve by gaining hands-on experience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling.
Job Description About Midea America Corp Midea America Corp., is one of the world's largest home appliance brands, offering the most comprehensive selection of products in the world to fully serve the needs of day-to-day living at home, at work, or anywhere else you go. In North America we strive to aim high, put the customer first, transform and innovate the marketplace, utilizing our commitment, dedication, inclusion, and partnership with our teams. Midea America is a subsidiary of the Midea Group, a global company with over 150,000 employees and operations in more than 195 countries. As a publicly listed company, we are ranked as a Fortune Global 500 company and offer one of the most comprehensive product portfolios in the industry. Job Summary The Senior Innovation Engineer is a key member of the Front-End Innovation and Product Development organization, responsible for identifying unmet consumer needs, incubating innovative technologies, and leading the development of next-generation microwave cooking solutions for the North American market. This role combines disruptive innovation, advanced engineering research, and product development activities to drive product differentiation across Over-the-Range Microwave Ovens (OTRs), Countertop Microwave Ovens (CMOs), combination ovens and emerging cooking platforms. The position focuses on translating consumer insights, market trends, competitive benchmarking, and emerging technologies into commercially viable products, features, and intellectual property that strengthen Midea's market leadership. The successful candidate will lead innovation initiatives from concept ideation, technology evaluation, and prototype development through commercialization, while serving as a technical expert in microwave cooking systems, ventilation systems, connectivity, and user experience. Essential Job Responsibilities Develop breakthrough product concepts, user experiences, and technology roadmaps that support future product platforms and strategic business growth. Conduct consumer research, competitive benchmarking, technology scouting, and trend analysis to identify opportunities for product differentiation and innovation. Lead the design, validation, and optimization of OTR ventilation systems, including blower configurations, airflow management, grease filtration, noise reduction, air recirculation, and outside venting solutions. Conduct airflow, acoustic, thermal, smoke-capture, and cooking-effluent performance evaluations to improve ventilation effectiveness and user experience. Design and develop microwave subsystems, including cavity systems, inverter technologies, high-voltage systems, controls, electronics, ventilation systems, and user interfaces. Lead the creation, evaluation, documentation, and protection of innovative technologies, product concepts, and intellectual property; develop invention disclosures, support patent filings, and build a robust patent portfolio that strengthens the company's competitive position. Partner with external technology providers, startups, universities, and suppliers to evaluate emerging technology opportunities and strategic collaborations. Mentor junior engineers and provide technical leadership across cross-functional project teams to accelerate innovation and product development effectiveness. Support domestic and international travel to collaborate with overseas R&D centers, suppliers, manufacturing facilities, attend trade shows, and consumer research activities. Qualifications Bachelor's degree in Engineering, Business, Product Management, Product Development, Data Analytics, Marketing, or a related discipline; Master's degree preferred. 7+ years of experience in product planning, product management, product development, engineering, innovation management, or portfolio management preferably within the cooking appliance industry. Proven experience developing product roadmaps, portfolio strategies, business cases, product requirements, and commercialization plans, translating consumer insights and market opportunities into successful products. Experience leveraging data analytics, business intelligence, AI-enabled insights, market research, consumer analytics, Voice of Customer Data, and competitive intelligence to support innovation and strategic decision-making. Proficiency with business intelligence, data visualization, and analytical tools such as Power BI, Tableau, SQL, Python, and AI-assisted analytics; experience with machine learning, predictive modeling and forecasting. Familiarity with North American appliance regulations, codes, and certification standards, including UL, CSA, ANSI, DOE, ENERGY STAR , and other applicable safety, performance, energy efficiency, and compliance requirements, is preferred. Strong project management, problem-solving, decision-making, communication, presentation, and interpersonal skills, with the ability to effectively communicate complex technical and business concepts to diverse audiences. Ability to influence and collaborate effectively across engineering, marketing, sales, sourcing, manufacturing, quality, and executive leadership teams. Experience working with global product development teams, international suppliers, and manufacturing organizations in a multicultural environment. Disclaimer This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities. Duties, responsibilities, and activities may change at any time with or without notice. EEO Statement We are an equal opportunity employer and value diversity. All employment is decided based on qualifications, merit, and business need.
10/25/2026
Full time
Job Description About Midea America Corp Midea America Corp., is one of the world's largest home appliance brands, offering the most comprehensive selection of products in the world to fully serve the needs of day-to-day living at home, at work, or anywhere else you go. In North America we strive to aim high, put the customer first, transform and innovate the marketplace, utilizing our commitment, dedication, inclusion, and partnership with our teams. Midea America is a subsidiary of the Midea Group, a global company with over 150,000 employees and operations in more than 195 countries. As a publicly listed company, we are ranked as a Fortune Global 500 company and offer one of the most comprehensive product portfolios in the industry. Job Summary The Senior Innovation Engineer is a key member of the Front-End Innovation and Product Development organization, responsible for identifying unmet consumer needs, incubating innovative technologies, and leading the development of next-generation microwave cooking solutions for the North American market. This role combines disruptive innovation, advanced engineering research, and product development activities to drive product differentiation across Over-the-Range Microwave Ovens (OTRs), Countertop Microwave Ovens (CMOs), combination ovens and emerging cooking platforms. The position focuses on translating consumer insights, market trends, competitive benchmarking, and emerging technologies into commercially viable products, features, and intellectual property that strengthen Midea's market leadership. The successful candidate will lead innovation initiatives from concept ideation, technology evaluation, and prototype development through commercialization, while serving as a technical expert in microwave cooking systems, ventilation systems, connectivity, and user experience. Essential Job Responsibilities Develop breakthrough product concepts, user experiences, and technology roadmaps that support future product platforms and strategic business growth. Conduct consumer research, competitive benchmarking, technology scouting, and trend analysis to identify opportunities for product differentiation and innovation. Lead the design, validation, and optimization of OTR ventilation systems, including blower configurations, airflow management, grease filtration, noise reduction, air recirculation, and outside venting solutions. Conduct airflow, acoustic, thermal, smoke-capture, and cooking-effluent performance evaluations to improve ventilation effectiveness and user experience. Design and develop microwave subsystems, including cavity systems, inverter technologies, high-voltage systems, controls, electronics, ventilation systems, and user interfaces. Lead the creation, evaluation, documentation, and protection of innovative technologies, product concepts, and intellectual property; develop invention disclosures, support patent filings, and build a robust patent portfolio that strengthens the company's competitive position. Partner with external technology providers, startups, universities, and suppliers to evaluate emerging technology opportunities and strategic collaborations. Mentor junior engineers and provide technical leadership across cross-functional project teams to accelerate innovation and product development effectiveness. Support domestic and international travel to collaborate with overseas R&D centers, suppliers, manufacturing facilities, attend trade shows, and consumer research activities. Qualifications Bachelor's degree in Engineering, Business, Product Management, Product Development, Data Analytics, Marketing, or a related discipline; Master's degree preferred. 7+ years of experience in product planning, product management, product development, engineering, innovation management, or portfolio management preferably within the cooking appliance industry. Proven experience developing product roadmaps, portfolio strategies, business cases, product requirements, and commercialization plans, translating consumer insights and market opportunities into successful products. Experience leveraging data analytics, business intelligence, AI-enabled insights, market research, consumer analytics, Voice of Customer Data, and competitive intelligence to support innovation and strategic decision-making. Proficiency with business intelligence, data visualization, and analytical tools such as Power BI, Tableau, SQL, Python, and AI-assisted analytics; experience with machine learning, predictive modeling and forecasting. Familiarity with North American appliance regulations, codes, and certification standards, including UL, CSA, ANSI, DOE, ENERGY STAR , and other applicable safety, performance, energy efficiency, and compliance requirements, is preferred. Strong project management, problem-solving, decision-making, communication, presentation, and interpersonal skills, with the ability to effectively communicate complex technical and business concepts to diverse audiences. Ability to influence and collaborate effectively across engineering, marketing, sales, sourcing, manufacturing, quality, and executive leadership teams. Experience working with global product development teams, international suppliers, and manufacturing organizations in a multicultural environment. Disclaimer This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities. Duties, responsibilities, and activities may change at any time with or without notice. EEO Statement We are an equal opportunity employer and value diversity. All employment is decided based on qualifications, merit, and business need.
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Summary The O&M Gas Systems Engineer supports the safe, reliable, and efficient operation of bulk and specialty gas delivery systems that enable semiconductor manufacturing. This role partners with Operations, Maintenance, Manufacturing, Safety, and Engineering teams to improve system reliability, troubleshoot complex equipment issues, drive continuous improvement initiatives, and support capital and operational projects while ensuring compliance with environmental, health, safety, and quality standards. The engineer leverages data analytics, AI-enabled tools, and digital technologies to enhance decision-making, optimize system performance, and improve operational efficiency. Responsibilities Support the operation, maintenance, and continuous improvement of bulk and specialty gas systems to ensure safe and reliable semiconductor manufacturing operations. Analyze system performance data, identify improvement opportunities, troubleshoot equipment issues, and lead root cause investigations to improve reliability and reduce risk. Utilize AI, machine learning, and advanced analytics tools to identify trends, predict equipment failures, optimize maintenance strategies, and enhance operational performance. Develop and implement digital solutions, dashboards, automated reporting, and data visualization tools that improve engineering efficiency and decision-making. Ensure compliance with Micron safety, environmental, quality, and change management requirements while promoting a strong safety culture. Partner with Operations, Maintenance, Manufacturing, and other stakeholders to resolve system issues, improve equipment performance, and support production goals. Lead and support engineering projects including equipment upgrades, new installations, commissioning activities, and reliability improvements. Develop and maintain engineering documentation, design standards, procedures, specifications, and preventive maintenance strategies. Utilize engineering principles, TPM methodologies, and data-driven insights to drive cost savings, efficiency improvements, and operational excellence. Provide technical guidance and support to cross-functional teams while effectively communicating project status, risks, recommendations, and data-driven conclusions. Minimum Qualifications Bachelor's degree in Engineering, Chemistry, Semiconductor Technology, or a related technical field, or equivalent combination of education and experience. Strong analytical and troubleshooting skills with the ability to identify root causes and implement effective corrective actions. Ability to work effectively in a cross-functional team environment and communicate technical information clearly to diverse audiences. Experience using engineering data, schematics, technical documentation, and standard problem-solving methodologies. Familiarity with data analytics, AI-assisted tools, or digital technologies used to support engineering, maintenance, or operational decision-making. Demonstrated commitment to safety, quality, and continuous improvement. Preferred Qualifications Experience supporting industrial utility systems, gas delivery systems, semiconductor facilities, or related manufacturing environments. Knowledge of high-purity gas systems, instrumentation and controls, mechanical systems, and reliability engineering principles. Experience applying AI, machine learning, predictive analytics, or digital engineering tools to improve equipment reliability, maintenance effectiveness, or operational performance. Experience leading projects, coordinating cross-functional teams, and managing multiple priorities simultaneously. Familiarity with TPM, FMEA, root cause analysis, risk assessment, and continuous improvement methodologies. Experience developing automated workflows, dashboards, reporting systems, or engineering solutions using tools such as Microsoft Copilot, Power BI, Power Automate, Python, SQL, CMMS, SAP, Maximo, or similar platforms. Experience using AI-assisted productivity and engineering tools to improve technical documentation, data analysis, troubleshooting, and operational decision-making. As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on . Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws. To learn about your right to work click here. To learn more about Micron, please visit For US Sites Only: To request assistance with the application process and/or for reasonable accommodations, please contact Micron's People Organization at or 1- (select option ) Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards. Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron. AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.
10/23/2026
Full time
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Summary The O&M Gas Systems Engineer supports the safe, reliable, and efficient operation of bulk and specialty gas delivery systems that enable semiconductor manufacturing. This role partners with Operations, Maintenance, Manufacturing, Safety, and Engineering teams to improve system reliability, troubleshoot complex equipment issues, drive continuous improvement initiatives, and support capital and operational projects while ensuring compliance with environmental, health, safety, and quality standards. The engineer leverages data analytics, AI-enabled tools, and digital technologies to enhance decision-making, optimize system performance, and improve operational efficiency. Responsibilities Support the operation, maintenance, and continuous improvement of bulk and specialty gas systems to ensure safe and reliable semiconductor manufacturing operations. Analyze system performance data, identify improvement opportunities, troubleshoot equipment issues, and lead root cause investigations to improve reliability and reduce risk. Utilize AI, machine learning, and advanced analytics tools to identify trends, predict equipment failures, optimize maintenance strategies, and enhance operational performance. Develop and implement digital solutions, dashboards, automated reporting, and data visualization tools that improve engineering efficiency and decision-making. Ensure compliance with Micron safety, environmental, quality, and change management requirements while promoting a strong safety culture. Partner with Operations, Maintenance, Manufacturing, and other stakeholders to resolve system issues, improve equipment performance, and support production goals. Lead and support engineering projects including equipment upgrades, new installations, commissioning activities, and reliability improvements. Develop and maintain engineering documentation, design standards, procedures, specifications, and preventive maintenance strategies. Utilize engineering principles, TPM methodologies, and data-driven insights to drive cost savings, efficiency improvements, and operational excellence. Provide technical guidance and support to cross-functional teams while effectively communicating project status, risks, recommendations, and data-driven conclusions. Minimum Qualifications Bachelor's degree in Engineering, Chemistry, Semiconductor Technology, or a related technical field, or equivalent combination of education and experience. Strong analytical and troubleshooting skills with the ability to identify root causes and implement effective corrective actions. Ability to work effectively in a cross-functional team environment and communicate technical information clearly to diverse audiences. Experience using engineering data, schematics, technical documentation, and standard problem-solving methodologies. Familiarity with data analytics, AI-assisted tools, or digital technologies used to support engineering, maintenance, or operational decision-making. Demonstrated commitment to safety, quality, and continuous improvement. Preferred Qualifications Experience supporting industrial utility systems, gas delivery systems, semiconductor facilities, or related manufacturing environments. Knowledge of high-purity gas systems, instrumentation and controls, mechanical systems, and reliability engineering principles. Experience applying AI, machine learning, predictive analytics, or digital engineering tools to improve equipment reliability, maintenance effectiveness, or operational performance. Experience leading projects, coordinating cross-functional teams, and managing multiple priorities simultaneously. Familiarity with TPM, FMEA, root cause analysis, risk assessment, and continuous improvement methodologies. Experience developing automated workflows, dashboards, reporting systems, or engineering solutions using tools such as Microsoft Copilot, Power BI, Power Automate, Python, SQL, CMMS, SAP, Maximo, or similar platforms. Experience using AI-assisted productivity and engineering tools to improve technical documentation, data analysis, troubleshooting, and operational decision-making. As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on . Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws. To learn about your right to work click here. To learn more about Micron, please visit For US Sites Only: To request assistance with the application process and/or for reasonable accommodations, please contact Micron's People Organization at or 1- (select option ) Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards. Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron. AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.
Job Description Job Description We are a growing IT company; a great place to start and grow your career! CCS is a leading technology consulting firm providing best in class solutions to our clients for over 45 years. Expressed simply in our tagline - Right People, Right Results, Right Careers! Our philosophy is, in fact, an obsession that drives our behavior, our culture and our work. It's why we put tremendous emphasis on hiring individuals that embody the principles that align with our obsession. We continue to successfully provide network integration, support services, products solutions, and applications services to our valued clients in the northeast. Our focus is simple our goal is to make technology easy and to help our clients use it as effectively as possible. OVERVIEW The Network and Systems Technician 2 provides hands-on, mid-level support to the Islip School District technology department across both infrastructure and end-user support. The role is roughly equivalent to a Junior Systems Administrator. It exists so that day-to-day network, server, virtualization and device issues are handled quickly and independently on site, keeping classrooms and district offices running while senior engineers stay focused on design and architecture work. This person adds to the success of the team by resolving issues from first report to resolution, keeping systems patched and documented, and reducing the volume of work escalated to senior staff over time. The result is fewer disruptions for teachers, students and administrators, and a stronger, more reliable service for the district. Salary Range: 95K - 105K What You'll Do: Networking and infrastructure: Manage and troubleshoot routing, switching and wireless connectivity across district buildings; diagnose outages and performance issues and document each fix. Server maintenance: Perform routine server maintenance, including database and software updates and patching; monitor server health and respond to alerts. Virtualization (VMware vCenter): Manage virtual machines, including creating, updating and removing snapshots, and adjust CPU, memory and storage allocation as needed. Endpoint management: Deploy policies and manage Windows devices in Microsoft Intune, Chromebooks in Google Admin Console and iPads in Jamf; support device deployment, patching and inventory through Endpoint Central. End-user support and asset management: Resolve staff and student tickets in ServiceDeskPlus, keep asset records accurate, and keep users informed through resolution. Ticket resolution times and the quality of communication with end users. Patch and maintenance compliance, with no missed maintenance windows. Accuracy of asset records and technical documentation. Recurring problems, by identifying root causes and fixing them rather than just closing tickets. Fewer disruptions to teaching and learning, and less escalation to senior staff over time. Works with the district technology department, senior network and systems engineers, teachers, students, building administrators and district leadership. Assists with network equipment installs, replacements and configuration changes under senior direction, and escalates design or architecture work and issues beyond scope. Supports device rollouts and summer refresh projects so they finish before the school year starts. What You'll Bring: 2 to 5 years of hands-on IT experience covering both infrastructure and end-user support. Experience supporting a K-12 school district environment is preferred. Solid proficiency troubleshooting routing, switching and wireless networks. Routine server maintenance, including software and database updates. Working from a ticketing system and keeping documentation current (ServiceDeskPlus training provided). VMware vCenter, especially snapshots and resource allocation. Microsoft Intune for policy deployment and Windows device management. Google Admin Console for Chromebook management. Jamf for iPad management. ManageEngine Endpoint Central or other Endpoint Central products. Works independently through issues from first report to resolution. Communicates clearly and patiently with non-technical staff, students and administrators. Organized and disciplined about documentation, asset records and follow-up. Knows when to escalate, and keeps users informed until an issue is closed. Customer-focused, dependable and comfortable in a busy school environment. SUCCESS MEASUREMENTS / EXPECTED OUTCOMES What success looks like Fewer disruptions for staff and students, and less escalation to senior staff over time. First 30 days Learns the district's network layout, buildings, key systems and escalation paths. Works tickets in ServiceDeskPlus and closes common end-user issues without help. First 90 days Troubleshoots routing, switching and wireless issues independently and documents each fix. Handles routine server updates and vCenter snapshot and resource tasks on schedule. Pushes policies and manages devices across Intune, Google Admin and Jamf with little oversight. Key metrics / KPIs Tickets resolved within agreed response and resolution targets (SLA attainment). Escalation rate to senior staff, trending down over time. Patch and maintenance compliance, with zero missed maintenance windows. Accuracy of ServiceDeskPlus asset records. Repeat-ticket rate, with recurring issues fixed at the root. User satisfaction with communication and resolution. How performance is evaluated 30- and 90-day check-ins against the milestones above, followed by regular performance reviews. ServiceDeskPlus reporting on SLA, volume, escalations and repeat issues. Feedback from district technology leadership, senior engineers and end users. On-time completion of device rollouts and summer refresh projects before the school year starts. CCS Offers: Competitive salaries Comprehensive benefits including: Medical and dental plans Company paid vision and short and long term disability plans Flexible spending programs including Healthcare, Dependent Care, Transit and Parking 401K with employer match Tuition reimbursement Onsite fitness center (or gym membership reimbursement for client or satellite based employees) Company paid life Insurance Paid holidays and vacation Technical certification gift card rewards program Come experience our unique culture and see how our "right people, right results" philosophy has led to our outstanding success! We are great place to start your IT career! EEO Statement: Custom Computer Specialists is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. To request a reasonable accommodation to apply for this position or to enable qualified individuals with disabilities to perform essential job functions, contact or .
10/22/2026
Full time
Job Description Job Description We are a growing IT company; a great place to start and grow your career! CCS is a leading technology consulting firm providing best in class solutions to our clients for over 45 years. Expressed simply in our tagline - Right People, Right Results, Right Careers! Our philosophy is, in fact, an obsession that drives our behavior, our culture and our work. It's why we put tremendous emphasis on hiring individuals that embody the principles that align with our obsession. We continue to successfully provide network integration, support services, products solutions, and applications services to our valued clients in the northeast. Our focus is simple our goal is to make technology easy and to help our clients use it as effectively as possible. OVERVIEW The Network and Systems Technician 2 provides hands-on, mid-level support to the Islip School District technology department across both infrastructure and end-user support. The role is roughly equivalent to a Junior Systems Administrator. It exists so that day-to-day network, server, virtualization and device issues are handled quickly and independently on site, keeping classrooms and district offices running while senior engineers stay focused on design and architecture work. This person adds to the success of the team by resolving issues from first report to resolution, keeping systems patched and documented, and reducing the volume of work escalated to senior staff over time. The result is fewer disruptions for teachers, students and administrators, and a stronger, more reliable service for the district. Salary Range: 95K - 105K What You'll Do: Networking and infrastructure: Manage and troubleshoot routing, switching and wireless connectivity across district buildings; diagnose outages and performance issues and document each fix. Server maintenance: Perform routine server maintenance, including database and software updates and patching; monitor server health and respond to alerts. Virtualization (VMware vCenter): Manage virtual machines, including creating, updating and removing snapshots, and adjust CPU, memory and storage allocation as needed. Endpoint management: Deploy policies and manage Windows devices in Microsoft Intune, Chromebooks in Google Admin Console and iPads in Jamf; support device deployment, patching and inventory through Endpoint Central. End-user support and asset management: Resolve staff and student tickets in ServiceDeskPlus, keep asset records accurate, and keep users informed through resolution. Ticket resolution times and the quality of communication with end users. Patch and maintenance compliance, with no missed maintenance windows. Accuracy of asset records and technical documentation. Recurring problems, by identifying root causes and fixing them rather than just closing tickets. Fewer disruptions to teaching and learning, and less escalation to senior staff over time. Works with the district technology department, senior network and systems engineers, teachers, students, building administrators and district leadership. Assists with network equipment installs, replacements and configuration changes under senior direction, and escalates design or architecture work and issues beyond scope. Supports device rollouts and summer refresh projects so they finish before the school year starts. What You'll Bring: 2 to 5 years of hands-on IT experience covering both infrastructure and end-user support. Experience supporting a K-12 school district environment is preferred. Solid proficiency troubleshooting routing, switching and wireless networks. Routine server maintenance, including software and database updates. Working from a ticketing system and keeping documentation current (ServiceDeskPlus training provided). VMware vCenter, especially snapshots and resource allocation. Microsoft Intune for policy deployment and Windows device management. Google Admin Console for Chromebook management. Jamf for iPad management. ManageEngine Endpoint Central or other Endpoint Central products. Works independently through issues from first report to resolution. Communicates clearly and patiently with non-technical staff, students and administrators. Organized and disciplined about documentation, asset records and follow-up. Knows when to escalate, and keeps users informed until an issue is closed. Customer-focused, dependable and comfortable in a busy school environment. SUCCESS MEASUREMENTS / EXPECTED OUTCOMES What success looks like Fewer disruptions for staff and students, and less escalation to senior staff over time. First 30 days Learns the district's network layout, buildings, key systems and escalation paths. Works tickets in ServiceDeskPlus and closes common end-user issues without help. First 90 days Troubleshoots routing, switching and wireless issues independently and documents each fix. Handles routine server updates and vCenter snapshot and resource tasks on schedule. Pushes policies and manages devices across Intune, Google Admin and Jamf with little oversight. Key metrics / KPIs Tickets resolved within agreed response and resolution targets (SLA attainment). Escalation rate to senior staff, trending down over time. Patch and maintenance compliance, with zero missed maintenance windows. Accuracy of ServiceDeskPlus asset records. Repeat-ticket rate, with recurring issues fixed at the root. User satisfaction with communication and resolution. How performance is evaluated 30- and 90-day check-ins against the milestones above, followed by regular performance reviews. ServiceDeskPlus reporting on SLA, volume, escalations and repeat issues. Feedback from district technology leadership, senior engineers and end users. On-time completion of device rollouts and summer refresh projects before the school year starts. CCS Offers: Competitive salaries Comprehensive benefits including: Medical and dental plans Company paid vision and short and long term disability plans Flexible spending programs including Healthcare, Dependent Care, Transit and Parking 401K with employer match Tuition reimbursement Onsite fitness center (or gym membership reimbursement for client or satellite based employees) Company paid life Insurance Paid holidays and vacation Technical certification gift card rewards program Come experience our unique culture and see how our "right people, right results" philosophy has led to our outstanding success! We are great place to start your IT career! EEO Statement: Custom Computer Specialists is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. To request a reasonable accommodation to apply for this position or to enable qualified individuals with disabilities to perform essential job functions, contact or .
Job Description Job Description CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . What You'll Do: This role sits within CoreWeave's Product organization, focused on building and scaling advanced networking capabilities that power AI, machine learning, and high-performance computing workloads. You will partner closely with Engineering, Infrastructure, Sales, Marketing, and Customer Experience teams to deliver highly scalable, performant, and reliable networking products that meet the needs of some of the most demanding workloads in the industry. About the Role: At CoreWeave, a leader in specialized cloud computing for AI, machine learning, and high-performance computing, we are seeking a Staff Product Manager to lead our networking product portfolio. As a Staff Product Manager, Networking, you will own the strategy and roadmap for CoreWeave's networking products. You will develop a deep understanding of the rapidly evolving networking landscape and translate market insights into a clear, forward-looking product vision. Your work will ensure CoreWeave continues to deliver best-in-class performance, scalability, and reliability across its platform. You will collaborate closely with cross-functional teams to develop new products and enhance existing offerings, ensuring alignment with technological advancements, customer expectations, and market trends. This is a highly visible role with significant influence over the future of CoreWeave's networking platform. Who You Are: 5+ years of experience in product management, with a strong focus on networking, infrastructure, or distributed systems-particularly in high-performance or AI-driven environments Deep expertise in networking technologies, including VPCs, Direct Connect, cross/multi-cloud interconnects, private connectivity services, NAT, and IP address management (IPAM) Strong understanding of hyperscale cloud networking, software-defined fabrics, and Tier-1 carrier ecosystems Proven experience leveraging colocation providers, Points of Presence (PoPs), Network-as-a-Service (NaaS), and transit partners to optimize for low-latency, high-performance infrastructure Experience designing secure private service endpoint architectures that enable seamless communication across distributed VPC environments Demonstrated ability to own product strategy, roadmap development, and end-to-end execution for complex, technically sophisticated products Strong analytical and decision-making skills, with a track record of using data, market research, and customer insights to drive product decisions Excellent leadership and communication skills, with the ability to align and motivate cross-functional teams Bachelor's degree in Computer Science, Engineering, Telecommunications, Business, or a related field (or equivalent practical experience) Preferred: Experience building or scaling networking products within cloud, hyperscale, or high-performance computing environments Background working closely with infrastructure or platform engineering teams Advanced degree or specialized coursework in networking or distributed systems Wondering if you're a good fit? We believe in investing in our people and value candidates who bring diverse experiences to our teams-even if you don't meet every requirement. You love defining product strategy in technically complex, fast-evolving domains You're deeply curious about emerging networking technologies and their role in enabling AI and HPC workloads You excel at turning market insights and customer needs into scalable, high-impact products Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast. We're in an exciting stage of hyper-growth that you will not want to miss. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is reflected in our core values: Be Curious at Your Core Act Like an Owner Empower Employees Deliver Best-in-Class Client Experiences Achieve More Together The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: Medical, dental, and vision insurance - 100% paid for by CoreWeave Company-paid Life Insurance Voluntary supplemental life insurance Short and long-term disability insurance Flexible Spending Account Health Savings Account Tuition Reimbursement Ability to Participate in Employee Stock Purchase Program (ESPP) Mental Wellness Benefits through Spring Health Family-Forming support provided by Carrot Paid Parental Leave Flexible, full-service childcare support with Kinside 401(k) with a generous employer match Flexible PTO Catered lunch each day in our office and data center locations A casual work environment A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. 1157, or (iv) asylee under 8 U.S.C. 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
10/19/2026
Full time
Job Description Job Description CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . What You'll Do: This role sits within CoreWeave's Product organization, focused on building and scaling advanced networking capabilities that power AI, machine learning, and high-performance computing workloads. You will partner closely with Engineering, Infrastructure, Sales, Marketing, and Customer Experience teams to deliver highly scalable, performant, and reliable networking products that meet the needs of some of the most demanding workloads in the industry. About the Role: At CoreWeave, a leader in specialized cloud computing for AI, machine learning, and high-performance computing, we are seeking a Staff Product Manager to lead our networking product portfolio. As a Staff Product Manager, Networking, you will own the strategy and roadmap for CoreWeave's networking products. You will develop a deep understanding of the rapidly evolving networking landscape and translate market insights into a clear, forward-looking product vision. Your work will ensure CoreWeave continues to deliver best-in-class performance, scalability, and reliability across its platform. You will collaborate closely with cross-functional teams to develop new products and enhance existing offerings, ensuring alignment with technological advancements, customer expectations, and market trends. This is a highly visible role with significant influence over the future of CoreWeave's networking platform. Who You Are: 5+ years of experience in product management, with a strong focus on networking, infrastructure, or distributed systems-particularly in high-performance or AI-driven environments Deep expertise in networking technologies, including VPCs, Direct Connect, cross/multi-cloud interconnects, private connectivity services, NAT, and IP address management (IPAM) Strong understanding of hyperscale cloud networking, software-defined fabrics, and Tier-1 carrier ecosystems Proven experience leveraging colocation providers, Points of Presence (PoPs), Network-as-a-Service (NaaS), and transit partners to optimize for low-latency, high-performance infrastructure Experience designing secure private service endpoint architectures that enable seamless communication across distributed VPC environments Demonstrated ability to own product strategy, roadmap development, and end-to-end execution for complex, technically sophisticated products Strong analytical and decision-making skills, with a track record of using data, market research, and customer insights to drive product decisions Excellent leadership and communication skills, with the ability to align and motivate cross-functional teams Bachelor's degree in Computer Science, Engineering, Telecommunications, Business, or a related field (or equivalent practical experience) Preferred: Experience building or scaling networking products within cloud, hyperscale, or high-performance computing environments Background working closely with infrastructure or platform engineering teams Advanced degree or specialized coursework in networking or distributed systems Wondering if you're a good fit? We believe in investing in our people and value candidates who bring diverse experiences to our teams-even if you don't meet every requirement. You love defining product strategy in technically complex, fast-evolving domains You're deeply curious about emerging networking technologies and their role in enabling AI and HPC workloads You excel at turning market insights and customer needs into scalable, high-impact products Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast. We're in an exciting stage of hyper-growth that you will not want to miss. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is reflected in our core values: Be Curious at Your Core Act Like an Owner Empower Employees Deliver Best-in-Class Client Experiences Achieve More Together The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: Medical, dental, and vision insurance - 100% paid for by CoreWeave Company-paid Life Insurance Voluntary supplemental life insurance Short and long-term disability insurance Flexible Spending Account Health Savings Account Tuition Reimbursement Ability to Participate in Employee Stock Purchase Program (ESPP) Mental Wellness Benefits through Spring Health Family-Forming support provided by Carrot Paid Parental Leave Flexible, full-service childcare support with Kinside 401(k) with a generous employer match Flexible PTO Catered lunch each day in our office and data center locations A casual work environment A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. 1157, or (iv) asylee under 8 U.S.C. 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Job Description Job Description Divergent is building the new industrial age. Every day, our teams design, manufacture, and assemble advanced systems for some of the world's most demanding industries. Our integrated engineering and manufacturing platform transforms complex designs into production-ready solutions, helping customers move faster, build smarter, and deliver critical systems when they matter most. Divergent is a qualified Tier 1 supplier to global automotive OEMs and supports leading U.S. aerospace and defense companies. Join us and help push the boundaries of what can be built. Purpose Divergent is transforming manufacturing through our Adaptive Production System (DAPS), revolutionizing how complex structures are designed, built, and assembled. We are seeking an experienced CMM Programmer to ensure the precision, repeatability, and quality of our manufactured components. This position is ideal for a seasoned metrology professional who excels in high-mix, high-precision environments and is passionate about pushing the boundaries of automated inspection and data-driven quality systems. The Role Metrology Programming & Execution Develop, optimize, and execute CMM programs using PC-DMIS on Hexagon systems to inspect precision components. Perform hands-on CMM operation and dimensional analysis for additively manufactured and machined parts. Interpret complex engineering drawings and GD&T to create accurate, repeatable measurement strategies. Collaborate with engineering, machining, and quality teams to resolve dimensional issues and improve manufacturability. Support development of automated and integrated inspection processes , connecting metrology data with manufacturing systems and analysis tools. Technical Collaboration & Knowledge Sharing Partner with technicians and engineers to improve understanding of measurement results, root-cause analysis, and CMM program intent. Contribute to the creation of standard work procedures and best practices for CMM programming and inspection across the organization. Provide technical feedback to support continuous skill growth within the quality and production teams. Process Improvement & Technology Advancement Continuously refine measurement strategies to reduce cycle time and enhance accuracy . Evaluate and integrate emerging metrology technologies , such as laser scanning, structured light, and non-contact inspection. Collaborate on fixturing design and tooling selection to improve repeatability and part accessibility. Ensure measurement practices comply with ISO 9001, AS9100, and IATF 16949 standards and internal quality processes. Basic Qualifications Ability to lawfully access information and technology that is subject to US export controls Advanced proficiency in CMM programming and metrology within a precision or high-mix manufacturing environment. Expert-level skill with PC-DMIS and Hexagon CMM systems (or equivalent). Strong understanding of GD&T and the ability to interpret and apply it to complex 3D geometries. Proven ability to troubleshoot and resolve metrology-related manufacturing challenges . Experience with standard precision tools (micrometers, calipers, bore gauges, surface plates). Analytical approach to data review, measurement variation, and process feedback . Excellent communication skills and ability to work cross-functionally in a collaborative engineering environment. Preferred Qualifications Experience with non-contact metrology (laser scanning, structured light, photogrammetry). Familiarity with Python, C++, or VB for data automation or process scripting. Experience integrating CMM data with MES, SPC, or CAD/CAM systems . Background in aerospace, defense, or high-performance automotive manufacturing . Additional Requirements Candidates will complete an on-site technical skills demonstration ( Work Environment Manufacturing and lab environments with frequent interaction across production, machining, and quality teams. Requires use of PPE (safety glasses, gloves, hearing protection) and adherence to all safety standards. Ability to lift up to 25 lbs and stand for extended periods during equipment setup or inspection. Compensation oAt Divergent, our pay range is based on the level of the job. For this role, we will consider candidates at levels T03 - T05 as evaluated through our interview process. T03 / Programmer III: $45.00 - $54.00 T04 / Programmer IV: $52.00 - $63.00 Pay Range $45-$63 USD What We Offer: Holistic Compensation Package: Enjoy a world-class compensation package that includes a competitive salary, equity plan, and discretionary results-based incentive bonus opportunities, ensuring you're truly valued for your contributions. Wellness and Time Off: Embrace a healthy lifestyle with paid vacation, sick time, and company holidays, including a year-end shutdown to recharge. We support growing families with paid parental leave, recognizing the importance of bonding time. Comprehensive Health and Wellness: Prioritize your well-being with our comprehensive health and wellness benefits, offering both HMO and Premium PPO options. Additionally, benefit from company-sponsored life insurance and short and long-term disability coverage for peace of mind. Investment in Growth: We're committed to your professional development. Take advantage of reimbursement opportunities for learning and development initiatives, empowering you to continuously expand your skill set and reach peak performance. Collaborative and High-Performing Environment: Join our collaborative, dynamic, and high-performing team within a fast-paced, mission-driven company. Together, we're disrupting the traditional manufacturing industry, fostering innovation, and integrating people and technology to reduce our footprint. Equal Employment Opportunity Divergent is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected characteristic. Divergent provides affirmative action in employment for qualified Individuals with Disabilities and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. EEO Poster In order to adjust to changes in our business, it may become necessary to add, remove or modify certain duties and responsibilities, or to reassign you to another job position. From time to time you may be asked to work on special projects or to assist with other work. Your cooperation and assistance in performing such additional work is expected. E-Verify: Right to Work Our company participates in E-Verify. E-Verify is a program that electronically confirms a candidate's eligibility to work in the United States after completing the Employment Eligibility Verification (Form I-9). The information provided on the Form I-9 is compared to the records contained in the Social Security Administration and Department of Homeland Security (DHS) databases. This helps employers verify the identity and employment eligibility of newly hired employees. Eligibility to Work Poster (English) Eligibility to Work Poster (Spanish) Los Angeles Fair Chance Initiative for Hiring Ordinance (FCIHO) Pursuant to the Los Angeles Fair Chance Initiative for Hiring Ordinance (FCIHO), we will consider for employment qualified applicants with arrest and conviction records. No agencies, no solicitations, and no calls please.
10/19/2026
Full time
Job Description Job Description Divergent is building the new industrial age. Every day, our teams design, manufacture, and assemble advanced systems for some of the world's most demanding industries. Our integrated engineering and manufacturing platform transforms complex designs into production-ready solutions, helping customers move faster, build smarter, and deliver critical systems when they matter most. Divergent is a qualified Tier 1 supplier to global automotive OEMs and supports leading U.S. aerospace and defense companies. Join us and help push the boundaries of what can be built. Purpose Divergent is transforming manufacturing through our Adaptive Production System (DAPS), revolutionizing how complex structures are designed, built, and assembled. We are seeking an experienced CMM Programmer to ensure the precision, repeatability, and quality of our manufactured components. This position is ideal for a seasoned metrology professional who excels in high-mix, high-precision environments and is passionate about pushing the boundaries of automated inspection and data-driven quality systems. The Role Metrology Programming & Execution Develop, optimize, and execute CMM programs using PC-DMIS on Hexagon systems to inspect precision components. Perform hands-on CMM operation and dimensional analysis for additively manufactured and machined parts. Interpret complex engineering drawings and GD&T to create accurate, repeatable measurement strategies. Collaborate with engineering, machining, and quality teams to resolve dimensional issues and improve manufacturability. Support development of automated and integrated inspection processes , connecting metrology data with manufacturing systems and analysis tools. Technical Collaboration & Knowledge Sharing Partner with technicians and engineers to improve understanding of measurement results, root-cause analysis, and CMM program intent. Contribute to the creation of standard work procedures and best practices for CMM programming and inspection across the organization. Provide technical feedback to support continuous skill growth within the quality and production teams. Process Improvement & Technology Advancement Continuously refine measurement strategies to reduce cycle time and enhance accuracy . Evaluate and integrate emerging metrology technologies , such as laser scanning, structured light, and non-contact inspection. Collaborate on fixturing design and tooling selection to improve repeatability and part accessibility. Ensure measurement practices comply with ISO 9001, AS9100, and IATF 16949 standards and internal quality processes. Basic Qualifications Ability to lawfully access information and technology that is subject to US export controls Advanced proficiency in CMM programming and metrology within a precision or high-mix manufacturing environment. Expert-level skill with PC-DMIS and Hexagon CMM systems (or equivalent). Strong understanding of GD&T and the ability to interpret and apply it to complex 3D geometries. Proven ability to troubleshoot and resolve metrology-related manufacturing challenges . Experience with standard precision tools (micrometers, calipers, bore gauges, surface plates). Analytical approach to data review, measurement variation, and process feedback . Excellent communication skills and ability to work cross-functionally in a collaborative engineering environment. Preferred Qualifications Experience with non-contact metrology (laser scanning, structured light, photogrammetry). Familiarity with Python, C++, or VB for data automation or process scripting. Experience integrating CMM data with MES, SPC, or CAD/CAM systems . Background in aerospace, defense, or high-performance automotive manufacturing . Additional Requirements Candidates will complete an on-site technical skills demonstration ( Work Environment Manufacturing and lab environments with frequent interaction across production, machining, and quality teams. Requires use of PPE (safety glasses, gloves, hearing protection) and adherence to all safety standards. Ability to lift up to 25 lbs and stand for extended periods during equipment setup or inspection. Compensation oAt Divergent, our pay range is based on the level of the job. For this role, we will consider candidates at levels T03 - T05 as evaluated through our interview process. T03 / Programmer III: $45.00 - $54.00 T04 / Programmer IV: $52.00 - $63.00 Pay Range $45-$63 USD What We Offer: Holistic Compensation Package: Enjoy a world-class compensation package that includes a competitive salary, equity plan, and discretionary results-based incentive bonus opportunities, ensuring you're truly valued for your contributions. Wellness and Time Off: Embrace a healthy lifestyle with paid vacation, sick time, and company holidays, including a year-end shutdown to recharge. We support growing families with paid parental leave, recognizing the importance of bonding time. Comprehensive Health and Wellness: Prioritize your well-being with our comprehensive health and wellness benefits, offering both HMO and Premium PPO options. Additionally, benefit from company-sponsored life insurance and short and long-term disability coverage for peace of mind. Investment in Growth: We're committed to your professional development. Take advantage of reimbursement opportunities for learning and development initiatives, empowering you to continuously expand your skill set and reach peak performance. Collaborative and High-Performing Environment: Join our collaborative, dynamic, and high-performing team within a fast-paced, mission-driven company. Together, we're disrupting the traditional manufacturing industry, fostering innovation, and integrating people and technology to reduce our footprint. Equal Employment Opportunity Divergent is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected characteristic. Divergent provides affirmative action in employment for qualified Individuals with Disabilities and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. EEO Poster In order to adjust to changes in our business, it may become necessary to add, remove or modify certain duties and responsibilities, or to reassign you to another job position. From time to time you may be asked to work on special projects or to assist with other work. Your cooperation and assistance in performing such additional work is expected. E-Verify: Right to Work Our company participates in E-Verify. E-Verify is a program that electronically confirms a candidate's eligibility to work in the United States after completing the Employment Eligibility Verification (Form I-9). The information provided on the Form I-9 is compared to the records contained in the Social Security Administration and Department of Homeland Security (DHS) databases. This helps employers verify the identity and employment eligibility of newly hired employees. Eligibility to Work Poster (English) Eligibility to Work Poster (Spanish) Los Angeles Fair Chance Initiative for Hiring Ordinance (FCIHO) Pursuant to the Los Angeles Fair Chance Initiative for Hiring Ordinance (FCIHO), we will consider for employment qualified applicants with arrest and conviction records. No agencies, no solicitations, and no calls please.