Top AI & Machine Learning Jobs in San Francisco, CA

Design and build AI agents, first-party web and mobile apps, and scalable backend services. Integrate LLM frameworks and enterprise systems, implement APIs and microservices, ensure observability and security, and collaborate with Finance, Security, and Engineering stakeholders.

Serve as the technical partner for net-new AI customers: design demos, lead end-to-end PoCs, architect and deploy production LLM applications, advise on best practices across infrastructure and tooling, and represent customer needs to shape product roadmap while partnering with sales and engineering.

Develop and run rigorous benchmarks and profiles for LLM inference workloads to identify bottlenecks and drive targeted performance optimizations across frameworks, runtimes, and GPU hardware. Design experiments (quantization, caching, speculative decoding), validate changes against real traces, partner with platform engineers to productionize improvements, and produce clear technical writeups to guide model-serving, runtime, and hardware decisions.

Lead and grow the engineering team productizing and operating an inference offering. Drive roadmap execution with Product, improve reliability, observability, release and incident processes, integrate platform capabilities, and deliver developer-friendly tooling and application-layer enhancements to scale production ML workloads.

Lead go-to-market and technical strategy for AI developer tooling, winning early customers and building repeatable playbooks. Translate customer MLOps requirements into product feedback, partner with engineering and Weights & Biases, and enable sales/solutions teams to close deals around experiment tracking, model governance, and LLM observability.

Lead and grow strategic partnerships across the Physical AI stack (robotics, simulation, autonomous systems). Drive joint product integrations, co-innovation, go-to-market motions, co-sell opportunities, and partner-aligned roadmaps with NVIDIA and key platform/OEM partners. Influence Product and Engineering requirements, execute quarterly business plans, and represent CoreWeave at industry events to accelerate revenue and market adoption.

As an Account Solutions Architect at CoreWeave, you'll partner with financial services customers to drive AI workload adoption, solve complex challenges, and expand relationships. You'll provide technical expertise, collaborate with stakeholders, and ensure customer success while working hands-on with advanced AI teams.

Lead cross-functional programs to validate and optimize AI/ML infrastructure performance. Drive benchmarking, observability, hardware bring-up, release readiness, and measurable metrics across GPU-based clusters. Coordinate engineering, infrastructure, product, capacity, and go-to-market teams to operationalize benchmarking frameworks, prioritize performance work, and ensure platforms meet stability and performance standards for training and inference workloads.

Sell and shape adoption of CoreWeaves AI Runtime Services by driving technical-commercial strategy, proving value with early customers, creating playbooks, and feeding product roadmap. Advise on serving frameworks, batching, execution isolation, throughput modeling, GPU utilization, and SLA structures while partnering with product, infra, and sales teams.

Lead and establish CoreWeave's Autonomous Vehicles field engineering vertical: design, build, validate, and deploy ML solutions and customer-facing applications using CoreWeave products. Drive complex customer engagements, translate field signals into product requirements, and set technical standards for perception, motion planning, simulation, and safety-focused AV development.