Senior Machine Learning Engineer (Generative AI, Python, Go, AWS)Capital One • United States

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Senior Machine Learning Engineer (Generative AI, Python, Go, AWS)

Capital One

United States

United States

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Join Our Team as a Senior Machine Learning Engineer! As a Senior Machine Learning Engineer on the Generative AI Workflows Serving team, you'll be part of an innovative Agile team dedicated to designing, building, and deploying cutting-edge Generative AI applications and Agentic Workflow systems at scale. You'll engage in detailed technical design, development, and implementation of complex machine learning applications leveraging cloud-native platforms. Your focus will be on creating robust ML serving architecture, developing high-performance application code, and ensuring high availability, security, and low latency of our Generative AI solutions. Collaboration with multiple AI/ML teams to drive innovation and continuously apply the latest best practices in machine learning engineering will be key to your role. Key Responsibilities: Design, build, and deliver Generative AI models and components that solve intricate business challenges while collaborating closely with Product and Data Science teams. Implement cloud-native ML Serving Platforms using cutting-edge technologies such as Docker, Kubernetes, KNative, and KServe for optimized and scalable model deployment. Tackle complex scaling and high-availability challenges by writing and testing high-performance application code in Python and Go, validating ML models, and automating tests and deployments. Adopt advanced MLOps and GitOps practices for continuous integration and continuous deployment (CI/CD), utilizing tools like ArgoCD for managing the entire lifecycle of models and applications. Leverage service mesh architectures like Istio to efficiently manage traffic, enhance security, and ensure resilience for high-volume serving endpoints. Maintain, monitor, and retrain models in production to ensure optimal performance. Construct optimized and scalable data pipelines that effectively feed ML models. Ensure code quality and governance to minimize vulnerabilities, while promoting Responsible and Explainable AI best practices. Utilize various programming languages including Python, Go, Scala, or Java. Basic Qualifications: Bachelor's Degree. A minimum of 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience not included). At least 4 years of programming experience with Python, Scala, Go or Java. A minimum of 2 years of experience in building, scaling, and optimizing ML systems. Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a related field. 3+ years of experience in building production-ready data pipelines that feed ML models. 3+ years of industry experience with recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow. 2+ years of experience in developing performant, resilient, and maintainable code. 2+ years of experience with data gathering and preparation for ML models. 2+ years of experience in a leadership role. 1+ years of experience leading teams in developing ML solutions using industry best practices, patterns, and automation. Experience with public cloud deployment, such as AWS, Azure, or Google Cloud Platform. Experience in designing, implementing, and scaling complex data pipelines for ML models while evaluating their performance. Contributions to the ML industry through conference presentations, papers, blogs, open source contributions, or patents. Please note that Capital One will not sponsor a new applicant for employment authorization or offer immigration-related support for this position. The role includes a competitive salary range and potential performance-based incentive compensation. Additional benefits supporting your total well-being are offered and vary based on employment status. This role is based in Cambridge, MA; McLean, VA; New York, NY; or San Francisco, CA. Capital One is an equal opportunity employer committed to compliance with applicable laws regarding criminal background inquiries.

United States

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English

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