Senior Distinguished Engineer, AI Compute

Job Description: Architect and build control and data plane implementations required to realize a highly available, multi-tenant, large scale and a secure machine learning platformDevelop Ray and Spark distributed compute engine solutions to accelerate diverse workloads from LLM pre-training and reinforcement learning to large-scale data processing, while maximizing compute unit economicsEngineer systemic improvements for operational excellence including automating KTLO (Keep The Lights On) workflowsDirect the technical execution of a diverse project portfolio, collaborating with developers specializing in everything ranging from distributed microservices to running large foundation modelsWork cross-functionally with product and program management disciplines, and stakeholder and partners across Capital One to help optimize business outcomes while driving towards strong technology solutionsShare your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and leading system design and code review sessionsHelp elevate the Capital One Distinguished Engineering community and establish yourself as a go-to resource on given technologies and technology-enabled capabilitiesLead the way in creating next-generation talent, mentoring internal talent and actively recruiting external talent to bolster the Capital One tech talent pool.Requirements: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologiesAt least 10 years of experience programming with Python, Go, Scala, or JavaMaster's Degree in Computer Science or a Master's Degree in Software Engineering (Preferred)Hands on experience in the internals of Ray (Actors/GCS/Scheduling) or Spark (Query Optimizer/Memory Management) (Preferred)Experience building platforms that support LLM training, fine-tuning, or high-throughput inference (Preferred)Hands-on experience with AWS-specific compute primitives (EKS, EC2 UltraClusters, Graviton) and cost-optimization strategies (Preferred)History of upstream contributions to major distributed systems projects (Preferred).Benefits: Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.