Description
We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team.
As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One.
Responsibilities:
- Design, build, and deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams
- Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale
- Inform ML infrastructure decisions using your 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 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
- Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI
- Use programming languages like Python, Scala, or Java
Basic Qualifications:
- Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field
- 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
- At least 6 years of experience using and operating large scale distributed systems
- At least 4 years of experience deploying and operating Machine Learning solutions in production
Preferred Qualifications:
- 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
- 5+ years of experience building resilient software solutions
- 5+ years of experience working with Machine Learning techniques
- 5+ years of experience designing, implementing, and scaling production-ready data pipelines
- 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
Salary Information:
- 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
- San Francisco, CA: $250,800 - $286,200
Benefits:
- Comprehensive, competitive, and inclusive set of health, financial and other benefits