Top Tech Jobs & Startup Jobs in San Francisco, CA

Designs, builds, tests, deploys, and supports AI software components for a GenAI platform, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Partners with engineers, researchers, TPMs, and product managers to deliver production AI systems and improve scalability, latency, throughput, cost, and hardware utilization.

Architects and scales AI compute infrastructure for Capital One’s machine learning platform, supporting distributed training, inference, and data processing workloads. Builds secure multi-tenant control and data plane systems, improves operational reliability, automates KTLO work, and optimizes compute economics. Leads technical execution across distributed systems, collaborates with product and program teams, mentors engineers, and helps recruit and elevate the engineering organization.

Build and deploy production AI systems, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Partner with engineers, researchers, TPMs, and product managers to deliver scalable, responsible AI solutions on cloud platforms, optimize performance and cost, and help define the technical vision for Capital One’s foundational AI infrastructure.

Lead AI/ML engineering for Capital One’s AI platform, building and supporting scalable AI software components such as foundation model training, LLM inference, similarity search, guardrails, experimentation, governance, and observability. The role also focuses on optimizing training and inference performance, partnering with engineering, research, TPM, and product teams, and shaping the long-term technical vision for foundational AI systems.

Lead applied research teams building and scaling AI foundation models for banking products. Partner with scientists, engineers, and product leaders to develop, train, evaluate, validate, and implement models. Guide and mentor applied scientists, represent Capital One in the research community, and translate research into business-impacting AI experiences.

Lead data engineering work for enterprise marketing and messaging platforms. Design, develop, test, implement, and support scalable cloud and data solutions using Python, Java, Scala, SQL, AWS, big data tools, and data warehouses. Collaborate with Agile teams and product managers, build distributed and real-time data systems, conduct code reviews and unit tests, and mentor other engineers while exploring AI-assisted development tools.

Lead development of foundational AI systems, including model training, LLM inference, guardrails, evaluation, governance, and observability. Partner with engineers, scientists, TPMs, and product managers to build scalable, responsible AI products. Optimize production AI performance for latency, throughput, cost, and hardware utilization while contributing to the long-term technical vision.

Build and optimize enterprise AI systems, including foundation models and LLM inference, for Capital One. Design, deploy, and support scalable, responsible AI components using cloud and open-source technologies, improve performance and cost, and help define the long-term AI roadmap.

Conduct applied AI research to build and improve foundation models for customer-facing products. Partner with data scientists, engineers, ML engineers, and product managers to design, train, evaluate, validate, and deploy scalable AI systems. Use modern deep learning and cloud technologies, translate research into business impact, and pursue an independent research agenda with publications and innovations.

Partners with cross-functional teams to research, develop, train, validate, and implement AI foundation models. Uses PyTorch, AWS, Hugging Face, Lightning, and vector databases to build scalable AI systems, improve customer experiences, and translate research into business impact.