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About the Role
Capital One is seeking Machine Learning Engineers passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to drive AI transformations and scale production models.
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 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, including test automation and monitoring, for successful deployment of ML models and application code.
- Ensure 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.
Requirements
- Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field.
- 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/ML 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 ML software systems.
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field.
- 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, model architectures, training concepts, and how to evaluate model accuracy and diagnose and address common issues.
- 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.
- Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences.
Skills
- Python
- Java
- Golang
- C++
- PyTorch
- Tensorflow
- Pandas
- NumPy
- Scikit-learn
- Spark
- Ray
- AWS
- GCP
- Azure
- Kubernetes
- Supervised learning
- Semi-supervised learning
- Unsupervised learning
- Reinforcement learning
- Regression
- Classification
- Clustering
- RNNs
- CNNs
- LSTMs
- Transformers
Location
- McLean, VA
- New York, NY
- Plano, TX
- Richmond, VA
Work Type
- Full-time
Experience Level
- 6+ years
- 4+ years
- 5+ years
Education Level
- Bachelor's Degree
- Master's Degree
- Doctoral Degree
Salary/Compensations
- McLean, VA: $229,900 - $262,400
- New York, NY: $250,800 - $286,200
- Plano, TX: $209,000 - $238,500
- Richmond, VA: $209,000 - $238,500
Benefits
- Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
- Eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
About the Company
- Capital One is a financial services company.
- Capital One is made up of several different entities, including Capital One Canada, Capital One Europe, and Capital One Philippines Service Corp. (COPSSC).
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 require an accommodation during the application process, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com.