8 jobs found

Set and drive strategies to transform operations planning business processes, focusing on schedule reliability, cost reduction and optimization; Influence leaders, squads and peers on strategy, technical feasibilities, DevOps best practices, software performance optimizations, roadmap items, OKRs and upcoming releases; Collaborate with internal teams, and Operations Research, IT and Network Planning teams to build the next generation of planning tools. Plan, organize, and direct the design, development, and implementation of enterprise planning products using cloud technologies, advanced analytics, and efficient workflow design; Design and optimize operational planning processes to improve operational performance; Design experiments, conduct feasibility studies, systems analysis, and technical economic assessments of various schedule constraints and operational standards; Mine, model, analyze, and evaluate operational data to identify root cause factors impacting network reliability; Play a key role in solving complex science problems which contribute to development of network schedules and operations plans; Coordinate process engineering projects across departments. Work closely with cross-functional teams to implement improvements; Contribute to the technical architecture and design of products by collaborating with engineering teams to ensure alignment with enterprise system architecture and cloud best practices; Collaborate with operational planning departments across divisions (Airport planning, Technical Operations/Maintenance, Integrated Operations Center Planning, Crew Planning), Operational leadership, and Network Planning in the development of future schedules and schedule solutions; Utilize technical analytics including A/B testing, product architecture, continuous deployment process, DevOps practices, data models and analytics, querying languages, tools supporting automation/metrics and other technologies in support of improved operational performance; Understand the budgetary implications and related organizational constraints in factoring areas of focus; Practice agility in discovering and delivering value continuously. Work Schedule: 40 hours per week/8 a.m.-5 p.m./M-F. Job Location: Fort Worth, TX Education and Experience Requirements Masters degree in Data Science, Business Analytics, or related field, plus 2 years of experience as Analyst, Product Owner, Specialist, Consultant, or any occupation in which the required experience was gained, and demonstrated experience in: Python Programming; SQL Programming; Airline Operations and Schedule Planning; Airline business model; Machine Learning and statistical Forecast Models for Airlines; Azure Databricks for automating workflows and data pipelines; Azure Data Factory; Azure DevOps; Tableau Dashboards for tracking performance; Test Driven Development; A/B Testing; Software Development; Data Analysis; Data Engineering. Please copy and paste your resume in the email body (do not send attachments, we cannot open them) and email it to candidates at (link removed) with reference in the subject line. Thank you.

Job Description Job Description Please Note: To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period. Advancing the World's Technology Together Our technology solutions power the tools you use every day including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you'll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what's possible and powering the future. We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We're dedicated to empowering people to be their true selves. Together, we're building a better tomorrow for our employees, customers, partners, and communities. Please Note: To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period. Advancing the World's Technology Together Our technology solutions power the tools you use every day including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you'll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what's possible and powering the future. We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We're dedicated to empowering people to be their true selves. Together, we're building a better tomorrow for our employees, customers, partners, and communities. The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. To achieve this goal, we collaborate closely with both hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of our systems. Additionally, we continuously conduct research and development in emerging technologies and trends across memory, computing, interconnect, and AI/ML, ensuring that our platforms are always equipped to handle the most demanding workloads of the future. By working together as a dedicated and passionate team, we aim to revolutionize the way AI/ML applications are deployed and executed, ultimately contributing to the advancement of AGI in an affordable and sustainable manner. Join us in our passion to shape the future of computing! Location: Daily onsite presence at our San Jose, CA office / U.S. headquarters in alignment with our Flexible Work policy. What You'll Do Develop IP for memory centric computing systems using Verilog, System Verilog and HLS Optimize the IP for performance, power, and area by leveraging advanced design techniques such as pipelining, parallelism, and data compression. Collaborate with Verification engineers to design and develop test plans Make design decisions out of a large design trade-off space across performance, power, thermal, and cost. Troubleshoot and debug hardware issues and ensure the quality of the design through verification and validation. Stay up-to-date with the latest advancements in machine learning and hardware architecture and contribute to the development of new technologies. Communicate effectively with stakeholders, including users, partners, and management, to ensure that the systems are delivered on time and within budget Complete other responsibilities as assigned. What You Bring Bachelor's with 5+ years, or Master's with 3+ years, or PhD's with 0+ years of industry experience. Strong background in microarchitecture and computer architecture 5+ years of experience in front-end design methodology involving RTL development for complex control and data path IPs Experience in designing Memory Controller, NOC, Interconnect IP Experience in Memory Centric computing IP and SOC integration Experience in AI/ML workloads. Strong analytical and problem-solving skills Excellent communication and interpersonal skills Ability to work independently and as part of a team You're inclusive, adapting your style to the situation and diverse global norms of our people. An avid learner, you approach challenges with curiosity and resilience, seeking data to help build understanding. You're collaborative, building relationships, humbly offering support and openly welcoming approaches. Innovative and creative, you proactively explore new ideas and adapt quickly to change. What We Offer The pay range below is for all roles at this level across all US locations and functions. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. We also offer incentive opportunities that reward employees based on individual and company performance. This is in addition to our diverse package of benefits centered around the wellbeing of our employees and their loved ones. In addition to the usual Medical/Dental/Vision/401k, our inclusive rewards plan empowers our people to care for their whole selves. An investment in your future is an investment in ours. Give Back With a charitable giving match and frequent opportunities to get involved, we take an active role in supporting the community. Enjoy Time Away You'll start with 4+ weeks of paid time off a year, plus holidays and sick leave, to rest and recharge. Care for Family Whatever family means to you, we want to support you along the way-including a stipend for fertility care or adoption, medical travel support, and virtual vet care for your fur babies. Prioritize Emotional Wellness With on-demand apps and free confidential therapy sessions, you'll have support no matter where you are. Stay Fit Eating well and being active are important parts of a healthy life. Our onsite Café and gym, plus virtual classes, make it easier. Embrace Flexibility Benefits are best when you have the space to use them. That's why we facilitate a flexible environment so you can find the right balance for you. Base Pay Range $138,000-$206,000 USD Equal Opportunity Employment Policy Samsung Semiconductor takes pride in being an equal opportunity workplace dedicated to fostering an environment where all individuals feel valued and empowered to excel, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status. When selecting team members, we prioritize talent and qualities such as humility, kindness, and dedication. We extend comprehensive accommodations throughout our recruiting processes for candidates with disabilities, long-term conditions, neurodivergent individuals, or those requiring pregnancy-related support. All candidates scheduled for an interview will receive guidance on requesting accommodations. Our Commitment to Innovation and Fairness At Samsung Semiconductor, we use Artificial Intelligence (AI) tools in the recruitment process to enhance efficiency. However, AI is used as a support tool, not a final decision-maker. All hiring decisions are made by our human recruiting team and hiring managers to ensure every candidate is evaluated fairly and holistically. Recruiting Agency Policy We do not accept unsolicited resumes. Only authorized recruitment agencies that have a current and valid agreement with Samsung Semiconductor, Inc. are permitted to submit resumes for any job openings. Applicant AI Use Policy At Samsung Semiconductor, we support innovation and technology. However, to ensure a fair and authentic assessment, we ask that candidates rely on their own knowledge and skills throughout the process. AI tools may be used for basic preparation, grammar, and research, but should not be used to generate or assist with submitted content or live interview responses. If we determine that AI is being used outside these guidelines, we reserve the right to pause or end the interview, and your candidacy may be disqualified. Trade Secret Notice By submitting an application, you agree not to disclose to Samsung-or encourage Samsung to use-any confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity. Applicant Privacy Policy - us/careers/us/privacy/

Job Description Job Description ABOUT US Do you have a passion for higher education? Do you want to make a positive impact on the college admissions process? Our staff help to remove barriers and encourage students to forge their path to a better future. Common App is a national not-for-profit organization dedicated to the pursuit of access, equity, and integrity in the college admission process. Each year we support more than 1 million students, one-third of whom are first-generation, as they apply to our more than 1100 diverse member colleges & universities using the Common App's free online application. If you are an experienced Artificial Intelligence professional and want to be part of a mission-driven non-profit that uses innovative technology to advance the college admission process, Common App may be a great match for you. Common App is currently searching for a Principal AI & Machine Learning Engineer. RESPONSIBILITIES The Principal Artificial Intelligence (AI) & Machine Learning (ML) Engineer is the technical leader responsible for embedding artificial intelligence into enterprise workflows and analytic processes to drive measurable gains in productivity, insight generation, and decision support within the Data Analytics & Research (DAR) division. Highly regarded for exceptional performance and deep technical expertise, this role focuses on applied, production-ready AI/ML, driving groundbreaking initiatives that embed artificial intelligence into enterprise workflows Reporting to the Senior Director, Analytics Engineering, the Principal AI/ML Engineer partners closely with Data Engineering, Data Governance, and cross-functional business stakeholders to ensure that AI solutions are scalable, secure, compliant, and aligned with enterprise data strategy. This role operates as a senior individual contributor and technical authority, setting standards for AI development practice, mentoring teammates on applied AI techniques, and translating complex machine learning capabilities into enterprise-grade systems that deliver lasting organizational value. The Principal AI/ML Engineer is a recognized expert in the field, frequently sought out for technical guidance, mentorship, and thought leadership both within the organization and across the broader AI and higher education data community. Requirements QUALIFICATIONS This role requires: Candidates must live in the United States. Hybrid Work & Travel: Employees can live anywhere in the US or its territories, with the willingness and ability to travel for periodic in-person events-including semi-annual Common App retreats, department retreats, and strategic leadership sessions. Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related quantitative or technical field; or an equivalent combination of education and experience. 8-10 years of progressive experience in machine learning, AI engineering, or data science, with at least 3 years focused on applied AI and production ML systems. Demonstrated experience integrating LLMs and generative AI into enterprise analytic or operational workflows. Demonstrated experience working within enterprise data governance and compliance frameworks. Expertise in applied machine learning and AI, including supervised and unsupervised learning, natural language processing, and large language model integration (e.g., OpenAI, Anthropic, open-source LLMs via Hugging Face). Demonstrated experience designing and deploying production-grade AI/ML systems, including end-to-end ML pipelines covering training, evaluation, versioning, deployment, and monitoring. Proficiency in R and Python for machine learning and AI development; familiarity with ML frameworks such as scikit-learn, PyTorch, TensorFlow, or equivalent. Experience building and operationalizing LLM-powered applications, including prompt engineering, retrieval-augmented generation (RAG), and tool/agent orchestration frameworks. Strong SQL skills and experience working with large-scale cloud data platforms (e.g., Databricks, Snowflake, BigQuery); ability to design AI-ready data pipelines within enterprise warehouse environments. Knowledge of AI governance, responsible AI principles, and compliance considerations for AI systems handling sensitive or personally identifiable data. Proven ability to serve as a senior technical individual contributor, setting standards, making architectural decisions, and mentoring peers without formal management authority. Strong interpersonal and communication skills, with the ability to translate complex AI/ML concepts into accessible language for non-technical stakeholders and executive audiences. Proven ability to manage multiple competing priorities and deliver high-quality AI solutions in a fast-paced, collaborative environment. The ideal candidate will possess: Master's or doctoral degree in Computer Science, Machine Learning, Data Science, or a related field. Relevant AI/ML or cloud certifications (e.g., Databricks Certified Machine Learning Professional, AWS Machine Learning Specialty, or equivalent). Experience working with Agile frameworks for cross-functional, product-minded collaboration. Experience with agentic AI frameworks. Familiarity with Databricks AI features, including MLflow, Model Serving, and Genie or semantic layer integrations. Experience in higher education, nonprofit, or mission-driven technology contexts. Advanced training in statistics, causal inference, or program evaluation methods. A passion for higher education is a plus. PAY RANGE $144,160 - $162,180 Benefits Common App is a virtual first environment. We value our employees' time and efforts. Our commitment to your success is enhanced by our competitive salary and an extensive benefits package including: Work-Life balance Virtual-first office Paid Time Off (PTO) Seven company-wide holidays Nine floating holidays Sick leave Monthly mental health day floating holidays prorated depending on start date Virtual-first support Choice of PC of MAC laptop May choose an external monitor, keyboard, mouse, and/or headset One-time office set-up stipend Monthly remote work stipend Monthly mobile stipend Financial security Market-based salaries Performance-based bonus 403(b) retirement plan 5% company contribution additional 5% company match 3-year vesting schedule Participation may begin immediately Health & wellness Choice of two health insurance plans Health Savings Account, depending on health plan selection Medical Flexible Savings Account, depending on health plan selection Vision insurance Dental insurance Insurance coverage begins on the date of hire Dependent Care Flexible Spending Account Maven virtual clinic for women's and family health Company provided life and ad&d insurance Opportunity to purchase additional life insurance for self, spouse, and dependents Company provided short and long-term disability insurance Career development Budgeted annual funds for professional development Growth opportunities within the company Additional perks Mutual of Omaha Employee Assistance Program Mutual of Omaha will preparation services Mutual of Omaha travel assistance Payroll dedication pet insurance through PinPaws 1Password family account We work to maintain the best possible environment for our staff, where people can learn and grow. We strive to provide a diverse, collaborative, team-oriented, creative environment where each person feels encouraged to contribute to our processes, decisions, planning, and culture. HOW DO I APPLY To apply for this opportunity, send your resume and cover letter with salary expectations. PROTECTING YOUR PERSONAL INFORMATION: During the recruiting process, please note that Common App will never: Provide a job offer without an interview Ask for payment to process documents, purchase equipment or for any other reason Request banking or credit card information Direct you to third-party services to obtain visas or other documentation As we work alongside you through our recruitment process, please remain alert and never provide financial information or payment to anyone claiming to offer a job opportunity. If you believe you're a victim of a job scam, report it to the Federal Trade Commission (FTC) or your state attorney general. To learn more about job scams, read the FBI's public service announcement or visit the FTC site.

Job Description Job Description As a Senior Network Security Engineer at Penumbra, you will play a critical role in determining the company's long term goals. You will be a key member of the Information Security and Compliance team. This is a highly technical, hands-on role. The Sr. Network Engineer will collaborate with Security, IT, Manufacturing, and Engineering teams and be responsible for engineering solutions and supporting operational activities across a hybrid cloud environment. The role responsibilities include ensuring compliance with legal and regulatory requirements and maintaining company security policies, standards, and industry's best practices. What You'll Work On • Ensure the network security of on-premises and cloud-based systems, networks, infrastructure, and services. • Enforce secure design standards and specifications for services, systems, and products. • Responsible for network security solutions, control designs, and enforcement across our environment. • Design and perform security assessments, configuration verification, configuration reporting, and other activities to validate control effectiveness. • Engage and share results of security audits with the Information Security and business partners to promote changes vital to improve risk posture. • Collaborate with cross-functional teams to develop and implement security measures supporting on-prem and cloud systems. • Develop roadmaps, standards, and documentation for technical solutions and existing configurations. Serve as the subject matter expert across the network security environment. • Respond to and lead, as appropriate, incident response activities for security incidents. • Collaborate with IT and line of business teams to integrate security into new and existing systems, processes, and initiatives. • Manage and configure security services, e.g., firewalls, intrusion detection/prevention systems, threat prevention technologies, VPNs, and other network security appliances. • Create and maintain documentation for security procedures, designs, and protocols, conduct security training and awareness for staff as appropriate to the role. • Stay current with emerging security threats and technologies in the security landscape. Ensure compliance with regulatory requirements and industry standards in the Company's environment. What You Contribute • A Bachelor's degree in computer science or related field with 10+ years of related experience, or equivalent combination of education and experience. • Master's degree preferred in Computer Science or Engineering with an emphasis in Computer Security or a related field • Highly analytical and results and process-oriented mindset strongly desired • 10+ years of hands-on design, enforcement and testing/validation of offensive security, defensive security, systems, and solutions engineering in a large enterprise • 5+ years of hands-on security experience with cloud platforms, i.e., Azure, AWS or Google Cloud Platform services, automation, or IaC • 5+ years of hands-on experience network security experience and expert-level knowledge on security technologies such as Palo Alto Firewalls, Cisco ISE, IPS, CASB, VPN management, SAML/OIDC NAC 802.1X, SIEM, SOAR, Radius/TACACS+, directory services • Proficient with network topologies, routing protocols, i.e., OSPF, BGP, ISIS, SDN, and tunneling technologies. • Proficient with diagramming and threat models, ability and competency to design and implement controls at scale based on risks • Proficient in conducting solutions architecture, security design reviews, passionate about security and privacy research, technologies, and methods. • Possess an understanding of past and emerging security exploits, threat actor motivations, and trends • Understanding security and compliance frameworks, security engineering, software delivery, and SDLC in a hybrid environment • Outstanding ethical standards and integrity. • Excellent communicator with strong oral, written, and interpersonal communication skills • High degree of accuracy and attention to detail • Proficiency with Microsoft Word, Excel, Visio, and PowerPoint • Excellent organizational skills with the ability to prioritize assignments while handling various projects simultaneously. Working Conditions General office environment. Willingness and ability to work on site. May have business travel up to 10%. Requires some lifting and moving of up to 10 pounds Must be able to move between buildings and floors. Must be able to remain stationary and use a computer or other standard office equipment, such as a printer or copy machine, for an extensive period of time each day. Must be able to read, prepare emails, and produce documents and spreadsheets. Must be able to move within the office and access file cabinets or supplies, as needed. Must be able to communicate and exchange accurate information with employees at all levels on a daily basis. Annual Base Salary Range: $146,000 - $220,000/ year We offer a competitive compensation package plus a benefits and equity program, when applicable. Individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. What We Offer • A collaborative teamwork environment where learning is constant, and performance is rewarded. • The opportunity to be part of the team that is revolutionizing the treatment of some of the world's most devastating diseases. • A generous benefits package for eligible employees that includes medical, dental, vision, life, AD&D, short and long-term disability insurance, 401(k) with employer match, paid parental leave, eleven paid company holidays per year, a minimum of fifteen days of accrued vacation per year, which increases with tenure, and paid sick time in compliance with applicable law(s). Penumbra, Inc., headquartered in Alameda, California, is a global healthcare company focused on innovative therapies. Penumbra designs, develops, manufactures, and markets novel products and has a broad portfolio that addresses challenging medical conditions in markets with significant unmet need. Penumbra sells its products to hospitals and healthcare providers primarily through its direct sales organization in the United States, most of Europe, Canada, and Australia, and through distributors in select international markets. The Penumbra logo is a trademark of Penumbra, Inc. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability, military or veteran status, or any other characteristic protected by federal, state, or local laws. If you reside in the State of California, please also refer to Penumbra's Privacy Notice for California Residents. For additional information on Penumbra's commitment to being an equal opportunity employer, please see Penumbra's AAP Policy Statement.

Job Description Job Description Job Description Principal Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home As a Principal Machine Learning Engineer, you are a deep technical authority responsible for designing and evolving the most critical ML systems in the company. The Principal Machine Learning Engineer will operate across training, inference, evaluation, and infrastructure, solving the hardest architectural and performance problems. While Technical Leads may own execution at the team level, you set the technical standard and shape how ML systems are built across the organization. This is a hands-on, high-impact role focused on depth. This position is 100% Remote. Principal Machine Learning Engineer Responsibilities: - Architect and build large-scale ML systems spanning data, training, evaluation, inference, and deployment. - Design reproducible, high-performance training pipelines across GPU infrastructure. - Architect inference systems that balance latency, throughput, cost, and reliability at scale. - Design and maintain data systems for high-quality synthetic and real-world training data. - Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership. - Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies. - Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products. - Make pragmatic trade-offs and ship improvements quickly, learning from real usage. - Work under real production constraints: latency, cost, reliability, and safety Principal Machine Learning Engineer Outcomes: - ML systems (training, inference, evaluation) are reliable, scalable, and meet defined performance targets. - Models deployed to production achieve measurable quality improvements and meet user-impact goals. - Production issues are proactively monitored, debugged, and resolved with clear root-cause analysis. - Team and cross-functional collaborators benefit from clear guidance, best practices, and scalable ML solutions. - Research-to-production cycles are efficient, safe, and continuously improve the product experience. Qualifications Principal Machine Learning Engineer Qualifications: - Strong background in deep learning and transformer-based architectures. - Artificial Intelligence (AI) experience required. - Hands-on experience training, fine-tuning, or deploying large-scale ML models in production. - Proficiency with at least one modern ML framework (e.g. PyTorch, JAX), and ability to learn others quickly. - Experience with distributed training and inference frameworks (e.g. DeepSpeed, FSDP, Megatron, ZeRO, Ray). - Strong software engineering fundamentals; you write robust, maintainable, production-grade systems. - Experience with GPU optimization, including memory efficiency, quantization, and mixed precision. - Comfort owning ambiguous, zero-to-one ML systems end-to-end. - A bias toward shipping, learning fast, and improving systems through iteration. - Experience with LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer. - Contributions to open-source ML or systems libraries. - Background in scientific computing, compilers, or GPU kernels. - Experience with RLHF pipelines (PPO, DPO, ORPO). - Experience training or deploying multimodal or diffusion models. - Experience with large-scale data processing (Apache Arrow, Spark, Ray). Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc. Looking to hire a Principal Machine Learning Engineer in San Francisco, CA or in other cities? Our IT recruiting agencies and staffing companies can help. We help companies that are looking to hire Principal Machine Learning Engineers for jobs in San Francisco, California and in other cities too. Please contact our IT recruiting agencies and IT staffing companies today! Additional Information Please check out all of our jobs at .

Lead Machine Learning Engineer (Manager IC) At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. 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 exceptional products for our customers. In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. 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: Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers. Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI. Fine-tune, develop and evaluate machine learning and foundation models, Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One. Leverage a broad stack of Open Source and SaaS AI technologies. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues. Retrain, maintain, and monitor models in production. Construct optimized data pipelines to feed ML models. 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. 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. You are a passionate communicator, comfortable with explaining complex technical concepts to non-technical partners across the business, sometimes in front of large audiences. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. 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 enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production Strategic & Business-Oriented: think beyond the technology, deeply understanding business needs and how AI can solve them. You don't just build; you strategize and prioritize work that delivers the greatest business value. Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team. Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem-solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions. Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities. A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 7+ years of experience designing, developing, delivering, and supporting AI services at scale 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation (RAG) 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or 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. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning 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 . click apply for full job details

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. 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 exceptional products for our customers. In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. 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: Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers. Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI. Fine-tune, develop and evaluate machine learning and foundation models, Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One. Leverage a broad stack of Open Source and SaaS AI technologies. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues. Retrain, maintain, and monitor models in production. Construct optimized data pipelines to feed ML models. 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. 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. You are a passionate communicator, comfortable with explaining complex technical concepts to non-technical partners across the business, sometimes in front of large audiences. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. 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 enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production Strategic & Business-Oriented: You think beyond the technology, deeply understanding business needs and how AI can solve them. You don't just build; you strategize and prioritize work that delivers the greatest business value. Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team. Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem-solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions. Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities. A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 7+ years of experience designing, developing, delivering, and supporting AI services at scale 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation (RAG) 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or 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. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning 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 . click apply for full job details

Lead Machine Learning Engineer (Manager IC) At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. 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 exceptional products for our customers. In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. 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: Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers. Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI. Fine-tune, develop and evaluate machine learning and foundation models, Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One. Leverage a broad stack of Open Source and SaaS AI technologies. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues. Retrain, maintain, and monitor models in production. Construct optimized data pipelines to feed ML models. 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. 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. You are a passionate communicator, comfortable with explaining complex technical concepts to non-technical partners across the business, sometimes in front of large audiences. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. 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 enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production Strategic & Business-Oriented: think beyond the technology, deeply understanding business needs and how AI can solve them. You don't just build; you strategize and prioritize work that delivers the greatest business value. Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team. Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem-solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions. Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities. A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 7+ years of experience designing, developing, delivering, and supporting AI services at scale 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation (RAG) 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or 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. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning 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 . click apply for full job details