Lead Machine Learning Engineer, Gen AI, Python, Go, AWS

Capital One

Lead Machine Learning Engineer at Capital One focusing on Generative AI applications and machine learning solutions. Designing scalable, cloud-native ML architecture while collaborating with various AI/ML teams.

Posted 5/1/2026full-timeSan Francisco • California, Massachusetts, New York, Virginia • 🇺🇸 United StatesSenior💰 $197,300 - $225,100 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoGoogle Cloud PlatformJavaKubernetesPythonPyTorchScalaScikit-LearnSparkTensorflow

About the role

Key responsibilities & impact

Design, build, and deliver GenAI models and components that solve complex business problems
Design and implement cloud-native ML Serving Platforms leveraging technologies like Docker, Kubernetes, KNative, and KServe
Solve complex scaling and high-availability problems by writing and testing performant application code in Python and Go-lang
Implement advanced MLOps and GitOps practices for continuous integration and continuous deployment (CI/CD) using tools like ArgoCD
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 and models follow best practices in Responsible and Explainable AI

Requirements

What you’ll need

Bachelor’s Degree
At least 6 years of experience designing and building data-intensive solutions using distributed computing
At least 4 years of experience programming with Python, Scala, Go or Java
At least 2 years of experience building, scaling, and optimizing ML systems
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field (preferred)
3+ years of experience building production-ready data pipelines that feed ML models (preferred)
3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred)
2+ years of experience developing performant, resilient, and maintainable code (preferred)
2+ years of experience with data gathering and preparation for ML models (preferred)
2+ years of people leader experience (preferred)
1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation (preferred)
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform (preferred)
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance (preferred)

Benefits

Comp & perks

Health insurance
401(k) matching
Flexible work hours
Paid time off
Professional development opportunities
Performance-based incentive compensation

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonGoScalaJavaMLOpsGitOpsCI/CDdata pipelinesML systemsResponsible AI

Soft Skills

people leadershipteam leadershipcommunication

Certifications

Bachelor's DegreeMaster's DegreeDoctoral Degree