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Our client, a leading innovator in autonomous mobility technology, is seeking a Product Data Analyst to join their dynamic team. As a Product Data Analyst, you will be an integral part of the Data Science and Product teams supporting vehicle performance analysis and customer experience enhancement. The ideal candidate will demonstrate strong analytical skills, excellent communication, and a passion for problem-solving, which will align successfully in the organization. Job Title: Product Data Analyst - Automotive Location: Foster City, CA Pay Range: $76 per hour What's the Job? Analyze vehicle, trip, and service performance data to surface trends, root causes, and opportunities that improve the end-to-end customer experience. Use SQL + Python (Pandas) to clean, transform, and validate large datasets; build analytics-ready tables/models with clear metric definitions. Develop and maintain dashboards and self-serve reporting in Looker and/or Databricks to support Product, leadership, and cross-functional stakeholders. Deliver ad hoc analyses to answer business questions, evaluate proposed product changes, and quantify impact (before/after, segmentation, cohort views). Partner with Product, Data Science, and Data Engineering to establish KPIs, align analysis to roadmap priorities, and communicate insights to non-technical audiences. What's Needed? Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, or related fields. Minimum of 4 years of experience in data analysis. Proficiency in SQL for data extraction, transformation, and analysis. Experience with Python and Pandas for data cleaning and manipulation. Ability to develop and maintain dashboards with visualization tools such as Looker, Tableau, or Power BI. What's in it for me? Opportunity to work at the forefront of autonomous vehicle technology and data-driven innovation. Engage in meaningful projects that directly impact customer experience and service quality. Collaborate with a talented and diverse team committed to excellence. Gain exposure to cutting-edge tools and techniques in data analysis and visualization. Be part of a forward-thinking organization that values continuous learning and growth. Upon completion of waiting period consultants are eligible for: Medical and Prescription Drug Plans Dental Plan Vision Plan Health Savings Account Health Flexible Spending Account Dependent Care Flexible Spending Account Supplemental Life Insurance Short Term and Long Term Disability Insurance Business Travel Insurance 401(k), Plus Match Weekly Pay If this is a role that interests you and you'd like to learn more, click apply now and a recruiter will be in touch with you to discuss this great opportunity. We look forward to speaking with you! About ManpowerGroup, Parent Company of: Manpower, Experis, Talent Solutions, and Jefferson Wells. ManpowerGroup (NYSE: MAN), the leading global workforce solutions company, helps organizations transform in a fast-changing world of work by sourcing, assessing, developing, and managing the talent that enables them to win. We develop innovative solutions for hundreds of thousands of organizations every year, providing them with skilled talent while finding meaningful, sustainable employment for millions of people across a wide range of industries and skills. Our expert family of brands - Manpower, Experis, Talent Solutions, and Jefferson Wells - creates substantial value for candidates and clients across more than 75 countries and territories and has done so for over 70 years. We are recognized consistently for our diversity - as a best place to work for Women, Inclusion, Equality and Disability and in 2023 ManpowerGroup was named one of the World's Most Ethical Companies for the 14th year - all confirming our position as the brand of choice for in-demand talent.

Our client, a leader in autonomous vehicle technology, is seeking a dedicated and innovative Machine Learning Engineer to join their dynamic team. As a Machine Learning Engineer, you will be an integral part of the Perception team supporting the development of advanced perception modules for autonomous systems. The ideal candidate will demonstrate strong problem-solving skills, a passion for cutting-edge technology, and excellent collaboration abilities, aligning seamlessly with the organization's mission to enhance safety and efficiency in autonomous transportation. Job Title: Machine Learning Engineer Location: Foster City, CA (Onsite in Foster City, CA at least 3 days onsite) Pay Range: $100 per hour What's the Job? Design and develop in-cabin Computer Vision machine learning modules for safety-critical perception and monitoring applications Implement perception model architectures and employ sophisticated training techniques Build high-quality datasets utilizing sensor inputs and large-scale data repositories Validate and optimize solutions through real-world driving scenarios to ensure safety and reliability Collaborate with cross-functional teams to integrate perception modules into autonomous systems What's Needed? Bachelor's Degree in Computer Science, Computer Engineering, or related field with 4+ years of relevant experience Strong background in modern Computer Vision and Machine Learning, including 3D reconstruction, detection, classification, and semantic segmentation Experience with training and deploying Deep Learning models Proficiency in C++ and/or Python programming languages Excellent communication skills and ability to work effectively in a team environment What's in it for me? Opportunity to work on innovative projects that directly impact safety and fleet efficiency Collaborate with a talented and passionate team of professionals Engage in continuous learning and professional development Contribute to the advancement of autonomous vehicle technology Be part of a forward-thinking organization committed to innovation and excellence Upon completion of waiting period consultants are eligible for: Medical and Prescription Drug Plans Dental Plan Vision Plan Health Savings Account Health Flexible Spending Account Dependent Care Flexible Spending Account Supplemental Life Insurance Short Term and Long Term Disability Insurance Business Travel Insurance 401(k), Plus Match Weekly Pay If this is a role that interests you and you'd like to learn more, click apply now and a recruiter will be in touch with you to discuss this great opportunity. We look forward to speaking with you! About ManpowerGroup, Parent Company of: Manpower, Experis, Talent Solutions, and Jefferson Wells. ManpowerGroup (NYSE: MAN), the leading global workforce solutions company, helps organizations transform in a fast-changing world of work by sourcing, assessing, developing, and managing the talent that enables them to win. We develop innovative solutions for hundreds of thousands of organizations every year, providing them with skilled talent while finding meaningful, sustainable employment for millions of people across a wide range of industries and skills. Our expert family of brands - Manpower, Experis, Talent Solutions, and Jefferson Wells - creates substantial value for candidates and clients across more than 75 countries and territories and has done so for over 70 years. We are recognized consistently for our diversity - as a best place to work for Women, Inclusion, Equality and Disability and in 2023 ManpowerGroup was named one of the World's Most Ethical Companies for the 14th year - all confirming our position as the brand of choice for in-demand talent.

Sr Lead Machine Learning EngineerAs a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: 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 At least 8 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 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ 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 performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences 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.New York, NY: $250,800 - $286,200 for Sr. 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 theCapital 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 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).

Senior Machine Learning Engineer (KServe + Kubernetes, building Kubernetes Clusters, PyTorch, TensorFlow)As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: 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 deploy 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 At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models 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.McLean, VA: $161,800 - $184,600 for Senior Machine Learning Engineer New York, NY: $176,500 - $201,400 for Senior 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 theCapital 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 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).

Senior Lead Machine Learning Engineer, (Intelligent Foundations & Experiences)As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: 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 At least 8 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 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ 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 performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences 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.McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer Richmond, VA: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. 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 theCapital 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 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).

Job Title: IT Software Engineer 4 Job Location: Chicago, IL, USA, 60603 Skills/Attributes: IAM,Java,Python,Spring,SQL,Ticketing Systems Position Description:Experience & Education Bachelors/Masters degree + 57 years experience OR Technical certification (no degree) + 8 years experience Desired (Nice-to-Have) Data management / data operations background Familiarity with ADO pipeline framework SRE (Site Reliability Engineering) experience Python scripting for automation Top Technical Skills (Required)1. 2+ years application support for cloud-based applications2. AEM (A e Experience Manager) / JavaScript / Angular / Spring Boot triaging issues3. Azure App Services, APIs, SQL Server DB4. High availability architecture expertise5. Monitoring tools: Thousand Eyes, App Insights, Grafana, etc. Soft Skills / Other Technical Python, PowerShell, SQL, JSON Knowledge of autoscaling features (no hands-on required) Daily Responsibilities Triage & resolve support tickets per SLA Critical application/technical problem identification & resolution Off-shift & weekend support calls Application availability & performance monitoring Develop scripts/automation to detect/correct issues Develop monitoring & alerting capabilities

About the Company Our client is building the first AI-native specialty medication access platform, transforming how patients, providers, and payers navigate complex specialty drug workflows. Their mission is to remove friction from medication access through intelligent automation, modern infrastructure, and thoughtful product design. They are seeking a Full-Stack Engineer with strong Python and React experience who wants meaningful ownership and the opportunity to build foundational systems in a fast-scaling health tech startup. What You'll Do Design, build, and maintain full-stack features using Python (backend) and React (frontend) Develop APIs and services that power core workflows in specialty medication access Build intuitive, high-performance user interfaces for providers, care teams, and operations staff Collaborate closely with Product, Design, and engineering teammates to translate complex healthcare workflows into scalable software solutions Write clean, maintainable, and well-tested code Participate in architectural discussions and influence core technical decisions Contribute to performance, reliability, and security best practices What They're Looking For 2+ years of professional experience as a full-stack engineer at a start-up Strong proficiency in Python (Django, FastAPI, Flask, or similar frameworks) Strong proficiency in React (modern hooks, state management, frontend best practices) Experience building and consuming RESTful APIs Familiarity with relational databases (e.g., PostgreSQL, MySQL) Comfort operating in startup environments and solving ambiguous problems Strong communication skills and ability to collaborate cross-functionally Nice to Have Experience in healthcare, health tech, or regulated environments Familiarity with cloud infrastructure (AWS, GCP, Azure) Experience with CI/CD pipelines and Docker Interest in AI-driven systems and intelligent automation This is an opportunity to help define the technical foundation of an AI-native healthcare platform with real-world impact on patient access and outcomes.

Lead Machine Learning EngineerAs a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: 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 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 systemsPreferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 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 2+ years of experience developing performant, resilient, and maintainable code 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 developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 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.McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer San Francisco, CA: $215,200 - $245,600 for Lead Machine Learning Engineer San Jose, CA: $215,200 - $245,600 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 theCapital 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 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).

Senior Technology Site Reliability EngineerCooley is seeking a Senior Site Reliability Engineer to join the Infrastructure & Development Operationsteam.Position summary: The Senior Technology Site Reliability Engineer("SRE") is responsible for ensuring the reliability, scalability, and performance of the firm's critical infrastructure and applications. The SREblends software engineering with systems engineering to build and maintain automated, resilient, and observable systems that support high availability and operational excellence. In addition to being technically advanced, the SRE will have a high degree of emotional intelligence and the ability to work as a team towards complex and layered objectives. Specific duties and responsibilities include, but are not limited to, the following:Position responsibilities: Monitor and maintain production systems to ensure high availability and performance Implement and manage service-level indicators (SLIs), objectives (SLO's), agreements (SLA's), and error budgets Participate in on-call rotations and incident response, including root cause analysis and postmortems Develop and maintain infrastructure as code (IaC) using Terraform Automate deployment, scaling, and recovery processes to reduce manual intervention Partner with DevOps to build and maintain CI/CD pipelines to support safe and efficient software delivery Implement observability solutions using metrics, logs, traces, and alerting systems (Prometheus, Grafana, DataDog, etc.) Proactively identify and resolve system bottlenecks and reliability risks Work closely with Infrastructure, DevOps, Development, and security teams to embed reliability into the development lifecycle Contribute to a culture of blameless post-mortems and continuous improvement Document operational procedures and share knowledge across teams All other duties as assigned or requiredSkills and experience:Required: After orientation at Cooley LLP, exhibit proficiency in the Microsoft Office suite, iManage and other firm applications Ability to work extended and/or weekend hours, as required Ability to travel, as required 6+ years direct applicable experience (e.g. site reliability engineering or related field) Proficiency in Terraform and programming languages such as Python, Go, or Java Deep expertise in cloud platforms, particularly AWS, and container orchestration Strong background in distributed systems, performance tuning, and automation Hands-on experience with configuration management tools such as Puppet, Chef, or SaltPreferred: Bachelor's Degree in Computer Science, Information Technology, Engineering, or associated discipline Experience working with advanced ETL data workflows including technologies such as AWS EMR, Azure Synapse, Azure Data Factory, or Apache Hive/Spark/Airflow Experience with IaC deployment of AKS/EKS/GKE architecture Experience with enterprise Data Lake environments using technologies such as DataBricks or SnowflakeCompetencies: Expert analytical/quantitative, problem-solving, and deductive reasoning skills, experience performing advanced troubleshooting and root cause analysis of complex technical issues Excellent organizational, planning, and time management skills and ability to work independently and in a team environment to manage competing priorities and meet deadlines Advanced verbal and written communication skills with the ability to present findings, conclusions, alternatives, and information clearly and concisely Experience working with all levels of business professionals, management, stakeholders, and vendors with the ability to build effective relationships through trust and diplomacyCooley offers a competitive compensation and excellent benefits package and is committed to fair and equitable employment practices.EOE.The expected annual pay range for this position with a full-time schedule is $140,000 - $205,000. Please note that final offer amount will be dependent on geographic location, applicable experience and skillset of the candidate.We offer a full range of elective benefits including medical, health savings account (with applicable medical plan), dental, vision, health and/or dependent care flexible spending accounts, pre-tax commuter benefits, life insurance, AD&D, long-term care coverage, backup care for children and/or adults and other parental support benefits. In addition to elective benefit options, benefited employees receive firm-paid life insurance, AD&D, LTD, short term medical benefits as well as 21 days of Paid Time Off ("PTO") and 10 paid holidays each year. We provide generous parental leave and fertility benefits. New employees will attend a detailed benefit orientation to learn more about our many benefits and resources.

Software Engineer for Risk Management Systems - Investment Management Location: Midtown Atlanta Hybrid: 4 days in office (with flex hours and days) Compensation: 125k - 140k base + 20k bonus PTO: unlimited Exceptional Benefits Overview Fullstack with an emphasis on Frontend performance Backend scalability Data visualization Design & develop enterprise scale applications and tools for portfolio managers. Troubleshoot and debug performance issues across base code, APIs, and data layers. Tech Stack Cloud Native: AWS Frontend: React, Redux, RTK Query, AG-Grid, MUI Backend: Java, Spring Boot, PostgreSQL, Redis, Snowflake DevOps: AWS EKS, CI/CD pipelines Skills & Qualifications 5+ years of enterprise software engineering experience Cloud-native development expertise Extensive React skills Proficiency in Java Spring or Python Strong AWS experience (Lambda, S3, EKS) Skilled in troubleshooting and debugging performance issues Experience in fintech, investment management, asset management, or similar domains BS or MS in Computer Science or related field

Sr. Distinguished Machine Learning EngineerOverview: As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You'll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.What you'll do in the role: Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems Lead large-scale ML initiatives with the customer in mind Leverage cloud-based architectures and technologies to deliver optimized ML models at scale Optimize data pipelines to feed ML models Use programming languages like Python, Scala, C/C++ Leverage compute technologies such as Dask and RAPIDS Evangelize best practices in all aspects of the engineering and modeling lifecycles Help recruit, nurture, and retain top engineering talentBasic Qualifications: Bachelor's degree At least 10 years of experience designing and building data-intensive solutions using distributed computing At least 7 years of experience programming in C, C++, Python, or Scala At least 4 years of experience with the full ML development lifecycle using modern technology in a business critical settingPreferred Qualifications: Master's Degree 3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models 3+ years of experience using Dask, RAPIDS, or in High Performance Computing 3+ years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn) Ability to communicate complex technical concepts clearly to a variety of audiences ML industry impact through conference presentations, papers, blog posts, or open source contributions Ability to attract and develop high-performing software engineers with an inspiring leadership styleCapital 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.McLean, VA: $314,800 - $359,300 for Sr Distinguished Machine Learning Engineer Plano, TX: $286,200 - $326,700 for Sr Distinguished 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 theCapital 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 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 CoverMyMeds CoverMyMeds is a leading healthcare technology company dedicated to helping patients get the medications they need more easily and efficiently. Through innovative platforms and collaborative partnerships, we remove barriers in the prescription process, making healthcare simpler and more accessible for everyone. Application Support Engineer ) We're looking for an Application Support Engineer to support and enhance our on-premise and cloud applications, ensuring reliable delivery, performance, and availability across our platforms. Position Summary In this role, you'll lead technical efforts to maintain, improve, and troubleshoot application services while mentoring teammates and driving operational excellence. Key Responsibilities Serve as a team leader and mentor. Design strategies to improve application availability, performance, and overall system health. Diagnose and resolve complex application issues. Perform root-cause analysis and implement long-term fixes. Identify and resolve recurring incidents to reduce mean time to resolution. Support application deployments and DevOps workflows. Create and refine processes to meet SLO/SLA targets. Develop, maintain, and automate Disaster Recovery documentation. Manage application-related data tasks, including SQL queries, stored procedures, and jobs. Participate in a 24/7 on-call rotation. Provide documentation and evidence for annual audits. Minimum Requirements Must be authorized to work in the U.S. (no sponsorship available). Bachelor's degree or equivalent experience; typically 4+ years of relevant work experience. Critical Skills Able to work independently and exercise sound judgment. 4-7+ years with Windows Server administration. 4-7+ years supporting both fat-client and web applications on Windows Server with SQL Server backends. 3+ years supporting system integrations (web services/APIs on IIS). 3+ years with automated build/provisioning processes. Scripting experience (PowerShell, Python, etc.) for application or cloud automation. 2+ years writing T-SQL and updating stored procedures. Preferred Skills Strong written and verbal communication skills. Ability to analyze complex systems with high attention to detail. Experience with public cloud providers (Azure, AWS, or GCP). Virtualization experience (VMware, Citrix). Familiarity with IT monitoring ( Solarwinds , LogicMonitor ) and APM tools (Datadog, Dynatrace). Experience with DevOps tools (Jenkins, Git, Rundeck , Terraform). Inclusive, team-focused leadership mindset. Cloud certification strongly preferred. 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 $110,400 - $184,000 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 welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process. If you require accommodation please contact us by sending an email to . Join us at McKesson!

Description Are you ready for a rewarding career challenge?Unleash your potential at Leidos, where we make smart smarter by delivering innovative technical, engineering, and science solutions through the efforts of our diverse and talented people who are dedicated to our customer's success. We empower our teams, contribute to our communities, and operate sustainably. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community. Our Mission, Vision, and Values guide the way we do business.If this sounds like an environment where you can thrive, keep reading!Are you a talented, creative, detail-oriented, tech comfortable, and people-focused learning designer looking for a fresh challenge? Your search ends here! We're seeking a full-time Instructional Technologist with the skills to design, develop, deliver and evaluate specialized and technical training for our dynamic clients. From engaging classroom instruction to online learning modules to experiential activities, you'll use your expertise to advance our clients' training missions.As a successful candidate, you'll make a difference by helping our clients build a comprehensive curriculum that expands their specialized knowledge and skills to improve their mission performance and make the world safer, healthier, and more efficient. Your communication skills and ability to help instructors and experts craft engaging learning environments and instruction that enables learners to feel present and ready for their training will increase learners' retention which will have a major impact on their ability to apply their learning to their jobs. Your ability to analyze requirements and then create effective and enriching learning interventions across a variety of mediums, platforms, and levels will support successful outcomes for our clients' missions. And your tech savvy will help our clients incorporate, evaluate, and implement the new tools and technologies that are changing our world.If you're ready to take your skills to the next level, we want to hear from you! Apply today and take the first step towards a fulfilling and rewarding career with Leidos.Your greatest work is ahead!Your Main Mission: Work as part of a team to support a dynamic specialized training program. Conduct consultations with instructors and course directors to determine instructional requirements, needs, and solutions and assist with course/content approval process. Manage training design and development projects including collaborating with technical designers to develop products in support of the training, reporting on progress, and using a database to track projects. Analyzing training requirements and designing and developing effective and engaging synchronous and asynchronous learning interventions. Document, update, and maintain course lesson plans. Develop and update online training content including WBTs, job aids, videos, podcasts, etc. Conduct training, when required, on instruction techniques, facilitate small-groups, and lead discussion sessions in classes in support of course instructors. Integrate technology, including AI tools and solutions, into content and into development workflows. Act as a role-player during training courses. Create new content and/or improve the design and delivery of existing instructor-led and online content. Collect and analyze quantitative and qualitative data in support of course/content evaluation and develop actionable recommendations based on the data for the continual improvement of the product/program. Facilitate small group discussions. Design, administer, and analyze the results of training-related surveys and assessments. Provide reporting on training activities as required. Execute diplomacy working with various levels of team members, managers, and customer to identify requirements and develop action plans. Partner cross-functionally with other team members, such as AV, IT, instructors, and production teams, to accomplish tasks and complete projects. Work with customers to coordinate resources, prioritize activities, and ensure quality and timely products. Utilize a project tracking tool and weekly meetings to track, communicate, and manage all tasks and projects to ensure all assigned tasks are completed or before the established due date. Archive projects per office-designated standards. Adhere to customer security policies and procedures regarding the use of systems, equipment, facilities, and infrastructure.What Sets You Apart: Possess a current TS/SCI with polygraph clearance. Hold a Bachelor's degree or higher and at least eight 8+ years (6+ with Master's Degree) of relevant work experience. Degrees in adult learning, education, online learning, or equivalent or a degree in computer science or equivalent with applied experience in instructional design, technology, or educational technology are preferred. Ability to learn technical skills and teach them to others. Experience or training using quantitative and qualitative evaluation methods. Demonstrated experience/ability to collect, analyze, and report on courses and their impact on learning to inform design decisions or projects. Experience with the ADDIE model of instructions design, or equivalent, as well as experience and familiarity with a broad range of adult learning theories and models for evaluation of adult learning. Demonstrated experience working with subject matter experts to analyze and determine learning requirements, design solutions, develop engaging content, and implement and evaluate a variety of training solutions. Ability to develop strategies for a variety of learning types and their delivery on a range of platforms. Demonstrated experience and knowledge developing online training and learning tools and the knowledge to be able to successfully differentiate the needs of online training from instructor-led training. Demonstrated ability to effectively incorporate accessible design concepts into learning products based on ADA compliance and experience. Demonstrated ability to initiate projects, determine how to effectively move them through to completion, and then to successfully complete those projects. A self-starter, who is highly organized and capable of setting and maintaining schedules for themselves and for others, including coordinating and communicating schedule elements. Demonstrated excellent interpersonal skills and ability to provide proactive customer service support. Strong written and oral communication skills with the ability to independently craft error-free, tone appropriate, and professional learning content, marketing, informational, and status communications in a variety of mediums and formats across a wide range of audiences. Demonstrated ability to work successfully individually, within a team, and across multidisciplinary teams. Familiarity with handling intellectual property and copyright materials and how to properly incorporate them into learning content. Experience utilizing project tracking mechanisms or learning management systems (LMS) to communicate, coordinate, prioritize, and complete projects on schedule. Experience using tools to create online learning products, e.g., Camtasia, Articulate Storyline, Lectora, etc. or Adobe products, HTML, or other programming languages; as well as an understanding and experience designing and developing ADA-compliant training products. Experience with the Microsoft Office Suite of products (e.g., MS Word, PowerPoint, or Excel).You Might Also Have: Hold a Master's degree in adult learning, education, or online learning, or equivalent. Programming experience in HTML, Python, Java, JavaScript and/or other languages in support of developing training content. Experience or training in fundamental data literacy, i.e., the able to input, process, clean and visualize data sets and records. Experience delivering high-quality classroom instruction that effectively conveys the skills and expertise outlined in the course objectives to students. Additional relevant certifications, e.g., instructor, facilitator, MBTI, etc. Experience creating content in multimedia software tools like Adobe Creative Suites. Experience or training in copy editing for print or screen publications.At Leidos, the opportunities are boundless. We challenge our staff with interesting assignments that allow them to thrive professionally and personally. For us, helping you grow your career is good business. We're excited to learn more about you, apply today!If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.Original Posting:January 15, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range:Pay Range $82,550.00 - $149,225.00The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law . click apply for full job details

Lead Machine Learning Engineer (Gen AI, Python, Go, AWS)As a Capital One Machine Learning Engineer (MLE) on the GenAI Workflows Serving team, you'll be part of an Agile team dedicated to designing, building, and productionizing Generative AI applications and Agentic Workflow systems at massive scale. You'll participate in the detailed technical design, development, and implementation of complex machine learning applications leveraging cloud-native platforms. You'll focus on building robust ML serving architecture, developing high-performance application code, and ensuring the high availability, security, and low latency of our Generative AI solutions. You will collaborate closely with multiple other AI/ML teams to drive innovation and continuously apply the latest innovations and best practices in machine learning engineering.What you'll do in the roleThe 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 deliver GenAI models and componentsthat solve complex business problems, while working in collaboration with the Product and Data Science teams. Design and implement cloud-native ML Serving Platforms leveraging technologies like Docker, Kubernetes, KNative, and KServe to ensure optimized and scalable deployment of models. Solve complex scaling and high-availability problems by writing and testing performant application code in Python and Go-lang, developing and validating ML models, and automating tests and deployment. Implement advanced MLOps and GitOps practices for continuous integration and continuous deployment (CI/CD) using tools like ArgoCD to manage the entire lifecycle of models and applications. Leverage service mesh architectures like Istio to manage traffic, enhance security, and ensure resilience for high-volume serving endpoints. Retrain, maintain, and monitor models in production. Construct optimized, scalable 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. Use programming languages like Python, Go, Scala or JavaBasic 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, Go or Java At least 2 years of experience building, scaling, and optimizing ML systemsPreferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 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 2+ years of experience developing performant, resilient, and maintainable code 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 developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 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 New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer San Francisco, CA: $215,200 - $245,600 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 theCapital 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 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).

Software Engineering Intern Myriad Genetics is a leading genetic testing and precision medicine company dedicated to advancing health and well-being for all. Our tests empower individuals with vital genetic insights and enable healthcare providers to better detect, treat and prevent disease. Our tests are powered by an automated sequencing lab and software thatcovers a fullhardware and software technology stack:robotics,automation, scientific compute, data pipelines, variant calling/interpretation (bioinformatics), data visualization, risk calculations (population genetics), electronic medical records (EMR), patient and doctor user experience (UX), and solving key workflow problems in large complex health systems.We are looking for Software Engineering Interns to work in the parts of this technology stack that they find most interesting and ship innovative software solutions to production to improve our ability to provide these critical genetic insights to providers and patients. Responsibilities: This is aREMOTE - WORK FROM HOMEposition with flex-work as an option if you are near a Myriad location.Candidates must be living in United States and must have green-card or US citizenship. We are looking for self-motivated interns with backgrounds in Computer Science or Computational Biology who are interested in joining our engineering teams to work on problems in this space. Our interns are fully embedded with our software or research teams. We pair interns directly with an engineer or scientist on their team to work on projects ranging from shipping patient-facing production code to working on new early R&D genomics products. Qualifications Genomic or biology background is not required! Solving problems in our space requires software skills and an internship is a great opportunity to learn more about genetics. Experience with an object-oriented programming language: such as Python or Java. Experience with Database (SQL or oracle) is a plus Experience with AWS is a plus Currently enrolled in school majoring in Computer Science, Electrical Engineering, or Mathematics; preference will be given to Juniors and Seniors. Have relevant non-traditional software experience such as personal software projects, coding bootcamps, research Available to work a minimum of 40 hours/week for a summer or fall internship (-3 months) Good communication skills. TO DISCOVER ALL THE REMARKABLE ADVANCEMENTS THROUGHOUT MYRIAD GENETICS, INC PLEASE VISIT: Myriad Autoimmune: Myriad Neuroscience: Myriad Oncology: Myriad Urology: Myriad Women's Health: For more information on how Myriad is making a difference, please visit the Company's website: For other great information, you can visit us on LinkedIn at: WE ARE AN EQUAL OPPORTUNITY EMPLOYER. All applicants will be considered for employment without attention to mental or physical disability, race, color, religion, sex, sexual orientation, gender identity, age, genetic information, national origin, disability status, military or veteran status. Applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder) We take geographic location into account when determining base salary to ensure equitable and competitive compensation.

Platform Engineer, Information Technology Overview NISA Investment Advisors, LLC (NISA) offers customized investment solutions for tax-exempt and taxable institutional clients. NISA manages over $298 billion in fixed income and equity securities and over $172 billion in derivative notional value. We seek bright, motivated individuals who can contribute to our growing team of professionals. Candidates with a high degree of independent thinking skills, strong analytical and quantitative skills, and team playing abilities are encouraged to apply. Responsibilities We are seeking a highly skilled Platform Engineer to join our dynamic team. You will play a critical role in designing, implementing, and maintaining scalable cloud infrastructure solutions. Your knowledge of CI/CD pipelines, Terraform, and AWS will be essential in optimizing and automating our deployment processes while ensuring reliability, security, and performance.Key Responsibilities: Build, and maintain CI/CD pipelines for efficient software delivery Develop and manage Infrastructure as Code (IaC) solutions using Terraform Deploy and maintain cloud infrastructure on AWS, ensuring scalability and security Automate provisioning, configuration, and monitoring of infrastructure. Work closely with development and operations teams to improve deployment strategies and system reliability Implement security best practices, ensuring compliance with industry standards Troubleshoot and resolve infrastructure-related issues efficiently Stay up to date with the latest industry trends and technologies to continuously improve the platform Qualifications Bachelor's degree or equivalent experience in a field requiring strong analytical and quantitative skills such as Computer Science, Engineering, Mathematics, Finance, or Information Systems preferred 3+ years of experience as a Platform Engineer, DevOps Engineer, or Cloud Engineer Experience in CI/CD tools (e.g., GitHub Actions (Preferred), Jenkins, GitLab CI/CD, or CircleCI) Hands-on experience with Terraform for Infrastructure as Code (IaC) Proficiency with AWS services (e.g., EC2, S3, IAM, Lambda, RDS, ECS, EKS) Scripting skills in Bash, Python, or similar language Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) Solid understanding of networking, security, and cloud architecture best practices Familiarity with monitoring and logging tools (e.g., Datadog (Preferred) Prometheus, Grafana, CloudWatch) Certifications such as AWS Certified Solutions Architect or Terraform Associate is a plus Experience with configuration management tools (e.g., Ansible, Chef, or Puppet) is a plus Knowledge of serverless computing and event-driven architectures Understanding of policy-as-code and compliance frameworks (e.g., AWS Config, Open Policy Agent) NISA's culture encourages collaboration and innovation. We seek self-motivated, intellectually curious individuals willing to push themselves and others in an environment that celebrates fresh thinking. We equip employees with the resources needed to excel and we encourage personal development. NISA is dedicated to internally cultivating and rewarding talent. Employees at NISA are provided with a wide range of benefits, including health, dental, vision and life insurance options, paid time off, a competitive retirement plan, onsite cafeteria, fitness center, a health and wellness program and an educational assistance program. NISA 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, disability, or protected veteran status.

Senior Lead, Machine Learning (GenAI, Python, AWS)As a Capital One Senior Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Operations, 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 At least 8 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 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ 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 performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences 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. Lead Machine Learning Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer Richmond, VA: $209,000 - $238,500 for Sr. 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 theCapital 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 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).

Senior Technology Site Reliability EngineerCooley is seeking a Senior Site Reliability Engineer to join the Infrastructure & Development Operationsteam.Position summary: The Senior Technology Site Reliability Engineer("SRE") is responsible for ensuring the reliability, scalability, and performance of the firm's critical infrastructure and applications. The SREblends software engineering with systems engineering to build and maintain automated, resilient, and observable systems that support high availability and operational excellence. In addition to being technically advanced, the SRE will have a high degree of emotional intelligence and the ability to work as a team towards complex and layered objectives. Specific duties and responsibilities include, but are not limited to, the following:Position responsibilities: Monitor and maintain production systems to ensure high availability and performance Implement and manage service-level indicators (SLIs), objectives (SLO's), agreements (SLA's), and error budgets Participate in on-call rotations and incident response, including root cause analysis and postmortems Develop and maintain infrastructure as code (IaC) using Terraform Automate deployment, scaling, and recovery processes to reduce manual intervention Partner with DevOps to build and maintain CI/CD pipelines to support safe and efficient software delivery Implement observability solutions using metrics, logs, traces, and alerting systems (Prometheus, Grafana, DataDog, etc.) Proactively identify and resolve system bottlenecks and reliability risks Work closely with Infrastructure, DevOps, Development, and security teams to embed reliability into the development lifecycle Contribute to a culture of blameless post-mortems and continuous improvement Document operational procedures and share knowledge across teams All other duties as assigned or requiredSkills and experience:Required: After orientation at Cooley LLP, exhibit proficiency in the Microsoft Office suite, iManage and other firm applications Ability to work extended and/or weekend hours, as required Ability to travel, as required 6+ years direct applicable experience (e.g. site reliability engineering or related field) Proficiency in Terraform and programming languages such as Python, Go, or Java Deep expertise in cloud platforms, particularly AWS, and container orchestration Strong background in distributed systems, performance tuning, and automation Hands-on experience with configuration management tools such as Puppet, Chef, or SaltPreferred: Bachelor's Degree in Computer Science, Information Technology, Engineering, or associated discipline Experience working with advanced ETL data workflows including technologies such as AWS EMR, Azure Synapse, Azure Data Factory, or Apache Hive/Spark/Airflow Experience with IaC deployment of AKS/EKS/GKE architecture Experience with enterprise Data Lake environments using technologies such as DataBricks or SnowflakeCompetencies: Expert analytical/quantitative, problem-solving, and deductive reasoning skills, experience performing advanced troubleshooting and root cause analysis of complex technical issues Excellent organizational, planning, and time management skills and ability to work independently and in a team environment to manage competing priorities and meet deadlines Advanced verbal and written communication skills with the ability to present findings, conclusions, alternatives, and information clearly and concisely Experience working with all levels of business professionals, management, stakeholders, and vendors with the ability to build effective relationships through trust and diplomacyCooley offers a competitive compensation and excellent benefits package and is committed to fair and equitable employment practices.EOE.The expected annual pay range for this position with a full-time schedule is $140,000 - $205,000. Please note that final offer amount will be dependent on geographic location, applicable experience and skillset of the candidate.We offer a full range of elective benefits including medical, health savings account (with applicable medical plan), dental, vision, health and/or dependent care flexible spending accounts, pre-tax commuter benefits, life insurance, AD&D, long-term care coverage, backup care for children and/or adults and other parental support benefits. In addition to elective benefit options, benefited employees receive firm-paid life insurance, AD&D, LTD, short term medical benefits as well as 21 days of Paid Time Off ("PTO") and 10 paid holidays each year. We provide generous parental leave and fertility benefits. New employees will attend a detailed benefit orientation to learn more about our many benefits and resources.