Design, build, and run machine learning systems at scale with a team that brings production operations, CI/CD discipline, and Responsible and Explainable AI into every model lifecycle. This full-time Machine Learning Engineer 4 (Manager, IC) role supports end-to-end work, from modeling and data pipelines to deployment, monitoring, and governance, with an emphasis on real-world business impact.
What you’ll do
The role overlaps across Ops, Modeling, and Data Engineering. You’ll contribute across one or more areas, including:
- Design, build, and deliver ML models and components that solve business problems in collaboration with Product and Data Science
- Guide ML infrastructure decisions using modeling knowledge across model and data selection, feature selection, 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 on 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 platforms to deliver optimized ML at scale
- Construct optimized data pipelines that feed ML models
- Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to support successful releases
- Manage code to reduce vulnerabilities, ensure risk-aware model governance, and follow Responsible and Explainable AI best practices
- Use programming languages such as Python, Scala, or Java
Required qualifications
- 2+ years of experience (minimum)
- Bachelor’s Degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
- At least 4 years programming with Python, Java, Golang, or C++
- At least 4 years ML experience using industry-standard frameworks and libraries (PyTorch or TensorFlow, plus Pandas, NumPy, Scikit-learn)
- At least 4 years operating large-scale distributed systems (Spark, Ray) to prepare AI or ML data
- At least 2 years deploying and operating ML solutions in production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large-scale containerized ML systems
Technologies you’ll work with
- Python, Scala, Java, Golang, C++
- PyTorch, Tensorflow, Pandas, NumPy, Scikit-learn
- Spark, Ray
- AWS, GCP, Azure, Kubernetes
Incentives and benefits
- Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI). Incentives may be discretionary or non-discretionary depending on the plan.
- Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits to support total well-being.
Location and salary
New York, NY (onsite). Salary range: $215,200 - $245,600 per year for Machine Learning Engineer 4.
Applications are expected to be accepted for a minimum of 5 business days. No agencies please.
Work authorization
At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration-related support for this position.
