Top AI & Machine Learning Jobs in San Francisco, CA

Conduct applied AI research and build foundation models through design, training, evaluation, validation, and production implementation. Collaborate with data scientists, software and machine learning engineers, and product managers to deliver scalable AI products. Research large deep learning models, optimization, self-supervised learning, robustness, explainability, and fine-tuning, while translating technical findings into business outcomes and pursuing an independent research agenda.

Lead the design, development, deployment, and support of scalable AI platform components, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, experimentation, and observability. Optimize AI training and inference for latency, throughput, cost, and hardware utilization. Partner with engineering, research, product, and program teams while contributing to technical strategy and mentoring stakeholders.

Lead the design, development, deployment, and support of foundational AI systems, including LLM inference, model training, similarity search, guardrails, evaluation, governance, and observability. Drive build-versus-buy decisions, optimize production AI systems for scalability, cost, latency, and throughput, and shape long-term technical roadmaps. Manage, mentor, and grow an engineering team while partnering with scientists, product managers, and technical program managers.

Conduct applied AI research and build foundation models across design, training, evaluation, validation, and deployment. Collaborate with data scientists, engineers, and product managers to deliver scalable AI-powered products. Research state-of-the-art methods in language and vision-language modeling, optimize training and inference, develop platform or solution code, and translate research findings into customer-focused business outcomes.

Lead development of responsible, scalable AI systems, including foundation-model training, LLM inference, similarity search, guardrails, evaluation, governance, experimentation, and observability. Optimize production AI systems for scalability, latency, throughput, hardware utilization, and cost. Partner with engineering, research, program management, and product teams while shaping the technical vision and roadmap for foundational AI platforms.

Design, develop, test, deploy, and support production AI systems, including foundation-model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI training and inference for scalability, latency, throughput, hardware utilization, and cost. Shape the technical vision and roadmap for foundational AI platforms while partnering with engineers, researchers, program managers, and product leaders. Mentor engineering teams and influence senior cross-functional stakeholders.

Designs, develops, tests, deploys, and supports foundational AI systems, including model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Develops optimization techniques to improve scalability, latency, throughput, hardware utilization, and cost. Partners with engineering, research, product, and program teams; contributes to technical vision and roadmaps; and mentors teams while applying emerging AI research to production systems.

Build and support foundational AI platform components, including LLM inference, model training, similarity search, guardrails, evaluation, governance, experimentation, and observability. Optimize large-scale AI systems for scalability, latency, throughput, hardware utilization, and cost. Contribute to technical strategy and roadmap, collaborate cross-functionally, and lead or mentor engineering teams while applying emerging AI research in production.

Build and lead development of an enterprise AI platform supporting large-scale AI-assisted analysis. Responsibilities include designing, developing, testing, deploying, and supporting foundation model training, LLM inference, similarity search, guardrails, evaluation, experimentation, governance, and observability. The role also requires advancing LLM optimization for scalability, latency, throughput, hardware utilization, and cost while shaping the long-term roadmap for foundational AI systems and mentoring engineering teams.

Lead the design, development, deployment, and support of foundational AI systems, including LLM inference, model training, similarity search, guardrails, evaluation, governance, and observability. Optimize production AI systems for scalability, cost, latency, throughput, and hardware utilization. Partner with engineers, scientists, program managers, and product managers while shaping the technical vision and roadmap for responsible AI platforms.