Sr. Director, Machine Learning Engineering (Remote-Eligible)
Core
Lead and scale a high-performing engineering organization responsible for the Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across Capital One products and services.
Role type
Sr. Director, Machine Learning Engineering (People & Technical Strategy)
Builds
Production-grade ML and GenAI systems, low-latency application-serving systems, and resilient data foundations for hyper-personalization.
Domain
Financial Services / AI & Machine Learning / Hyper-Personalization
Deliverable
production ML models | infrastructure
Required skills
People leadership (5+ years), technical strategy definition, MLOps governance, cloud-native engineering, team scaling, build-vs-buy decisions, cross-functional partnership, incident management, talent density management.
Preferred skills
7+ years managing engineering teams, 8+ years deploying scalable AI on major clouds, personalization platform expertise, Python/Java/C++/Golang, ML frameworks (PyTorch/TensorFlow), orchestration tools (Databricks/Airflow/Kubeflow), LLM optimization, containerization (Docker/Kubernetes), CI/CD.
Technologies
AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, TensorFlow, Databricks, Airflow, Kubeflow, Docker, Kubernetes.
Responsibilities
Define technical strategy and delivery roadmap for recommendation systems, ranking, decisioning, GenAI infrastructure, and MLOps; Build, develop, and manage engineers and engineering leaders; Partner cross-functionally to align strategy and prioritize investments; Drive design and operation of robust ML infrastructure and pipelines; Architect low-latency, event-driven systems for real-time personalization; Guide adoption of state-of-the-art AI and LLM optimization techniques; Provide organizational technical and people leadership by influencing architecture and mentoring managers/tech leads.
Seniority
Senior, hands-on IC with significant people leadership scope
