onsite
Sr. Distinguished Machine Learning Engineer - Capital One
ML Engineer
Lead the design, development, and productionization of large‑scale machine learning systems using Python, AWS, and deep learning frameworks, while mentoring teams and driving best practices for data engineering and model deployment.
About the role
Key Responsibilities
- Architect and implement end‑to‑end machine learning pipelines that scale to millions of users, leveraging AWS services such as SageMaker, Lambda, and ECS.
- Lead cross‑functional teams in the detailed technical design of ML applications, ensuring robust model training, validation, and deployment workflows.
- Mentor and coach engineers on best practices in data engineering, feature engineering, and model monitoring.
- Collaborate with product and data science stakeholders to translate business problems into scalable ML solutions.
- Drive continuous improvement of model performance, latency, and cost efficiency through experimentation and A/B testing.
Requirements
- 10+ years of experience in machine learning engineering, with a strong background in deep learning and large‑scale distributed systems.
- Proficiency in Python, SQL, and cloud-native ML tools (AWS SageMaker, TensorFlow, PyTorch).
- Hands‑on experience with data engineering pipelines, feature stores, and model serving at scale.
- Excellent communication skills and a proven track record of leading technical teams.
- Strong analytical mindset and ability to solve complex problems in a fast‑paced environment.
Skills
pythonmachine learningawsdeep learning