Top Tech Jobs & Startup Jobs in San Francisco, CA

Leads applied AI research and foundation model development for banking products. Partners with scientists, engineers, and product leaders to design, train, evaluate, validate, and implement large-scale AI systems. Represents Capital One in the research community, mentors applied scientists, and turns cutting-edge research into production AI experiences using tools like PyTorch, AWS, Hugging Face, and vector databases.

Conduct applied AI research focused on foundation models, partnering with data scientists, software engineers, machine learning engineers, and product managers to build trustworthy AI systems. Develop, train, evaluate, validate, and implement large models using tools like PyTorch, Hugging Face, Lightning, AWS UltraClusters, and vector databases. Translate research into scalable customer-facing products, contribute to libraries and platform code, and pursue an independent research agenda with high-impact outcomes.

Designs, develops, tests, deploys, and supports generative AI platform services, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimizes large-scale AI systems for performance, latency, throughput, cost, and hardware utilization while partnering with engineers, scientists, TPMs, and product managers.

Build and support Workday platform solutions for HR systems, including HCM, Recruiting, Compensation, Payroll, and Benefits. Develop integrations and API-based solutions, troubleshoot production issues, improve business processes, maintain documentation, and collaborate with HR, product, and technical stakeholders to deliver and support resilient Workday capabilities.

Lead development of AI systems and infrastructure for foundation models, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Partner with engineering, research, TPM, and product teams to deliver scalable, responsible AI products and optimize training and inference performance for production use.

Designs, develops, tests, deploys, and supports AI foundations and LLM systems, including model training, inference, similarity search, guardrails, evaluation, governance, and observability. Optimizes large-scale production AI for latency, throughput, cost, and hardware utilization. Partners with engineers, researchers, TPMs, and product managers to build responsible, scalable AI capabilities and influence the long-term AI roadmap.

Lead applied AI research and foundation model development, partnering with scientists, engineers, and product teams to build scalable AI-powered customer experiences.