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About the Role
As a Machine Learning Engineer at Capital One, you will be instrumental in driving AI transformations and scaling production models. You will leverage cutting-edge open-source frameworks, advanced algorithms, and emerging technologies to solve complex business problems in a fast-paced, collaborative environment.
Responsibilities
- Design, build, and/or deliver ML models and components that solve real-world business problems, in collaboration with Product and Data Science teams.
- Build and scale massive multi-tenant platforms for large footprint ML model training and/or serving.
- Inform ML infrastructure decisions using an understanding of ML modeling techniques and issues.
- 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 for 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 for 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 ML follows best practices in Responsible and Explainable AI.
- Use programming languages like Python, Scala, or Java.
- Serve as a force-multiplier for the team, balancing technical contribution with mentoring and elevating the skills of peers and junior engineers.
- Recruit, nurture, and retain top engineering talent.
- Share passion for staying on top of tech trends, experimenting with new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community.
Requirements
- Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
- At least 6 years of experience programming with Python, Java, Golang, or C++.
- At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn).
- At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data.
- At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems.
- At least 1 year of people leadership experience.
- Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field.
- 3+ years of experience managing and leading an ML engineering team.
- 5+ years of experience optimizing ML algorithms, configurations, and infrastructure.
- 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc.
- 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques, monitoring, alarms, and preparing incident response plans.
- 5+ years of experience working with Machine Learning techniques, model types, training concepts, and model evaluation.
- 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
- ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
Skills
- Python
- Java
- Golang
- C++
- PyTorch
- Tensorflow
- Pandas
- NumPy
- Scikit-learn
- Spark
- Ray
- AWS
- GCP
- Azure
- Kubernetes
- Machine Learning
- Data Engineering
- CI/CD
- Responsible AI
- Explainable AI
Location
- McLean, VA
- New York, NY
- Plano, TX
- San Francisco, CA
Work Type
- Full-time
Experience Level
- Senior Manager
- 6+ years programming experience
- 6+ years Machine Learning experience
- 6+ years distributed systems experience
- 4+ years production ML deployment experience
- 1+ year people leadership experience
- 3+ years ML team management experience
- 5+ years ML algorithm optimization experience
- 5+ years software development best practices experience
- 5+ years resilient software solutions experience
- 5+ years ML techniques experience
- 5+ years data pipeline experience
Education Level
- Bachelor's Degree in Computer Science, Machine Learning or a related quantitative field
- Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
Salary/Compensations
- McLean, VA: $229,900 - $262,400
- New York, NY: $250,800 - $286,200
- Plano, TX: $209,000 - $238,500
- San Francisco, CA: $250,800 - $286,200
Benefits
- Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
About the Company
- At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs.
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
- This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
- Capital One Financial is made up of several different entities.
Equal Opportunity
- 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.
- 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com.
- For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com.