Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Leads engineering teams building responsible, scalable AI systems and products. Oversees foundation model training, LLM inference, similarity search, guardrails, evaluation, experimentation, governance, observability, and production deployment. Makes build-versus-buy decisions across AI technologies, develops LLM optimization techniques, shapes foundational AI roadmaps, and recruits and mentors engineering talent. Partners with research, engineering, product, and program teams to deliver high-performance AI capabilities.

Leads resiliency and reliability engineering programs, identifying and mitigating technical risks across delivery. Builds scalable, highly available distributed systems and cloud-based services; drives observability, incident response, disaster recovery, chaos engineering, and reliability initiatives. Owns technical vision, coordinates large cross-functional teams, removes blockers, and delivers business impact. Develops TPM talent, strengthens the TPM practice, and influences product, engineering, design, and data science decisions in a regulated environment.

Lead the design, development, deployment, and support of foundational AI systems, including LLM training and inference, similarity search, guardrails, evaluation, governance, and observability. Develop optimization techniques that improve scalability, cost, latency, throughput, and hardware utilization. Partner with engineering, research, product, and program teams while contributing to AI platform strategy, technical vision, and long-term roadmaps.

Leads product strategy and a product management team for enterprise AI/ML and machine learning platforms. Defines Generative AI and ML platform vision, evolves capabilities for data scientists and software developers, drives platform adoption, and partners with adjacent platform leaders on an integrated ecosystem. The role requires deep technical expertise in AI/ML infrastructure, Generative and Agentic AI, cloud and open-source technologies, people leadership, and AI risk management.

Lead design, development, deployment, and support of scalable GenAI platform components (foundation model training, LLM inference, vector search, guardrails, evaluation, observability). Optimize training and inference performance, contribute to technical vision and roadmap, and partner with cross-functional teams to deliver responsible, production-grade AI systems.

Lead modernization of enterprise AI/ML infrastructure and analyst workflows. Build agentic, scalable, secure platform services, integrate generative AI and low-code/no-code tooling, scale AutoML for tabular and time-series, and engineer automated governance and controls while mentoring teams and influencing cross-functional stakeholders.

As an Applied Researcher I, you'll work with cross-functional teams to develop AI-powered products, engage in applied research, and build foundation models using various technologies.

This role involves leading the development of AI-powered products, optimizing large scale AI systems, and mentoring cross-functional teams. It focuses on designing and deploying AI components, contributing to the technical vision, and applying cutting-edge AI techniques.

Lead design, development, deployment, and support of foundational AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, and observability. Optimize large-scale AI performance (cost, latency, throughput), partner cross-functionally, and contribute to technical vision and roadmap.

As an Applied Researcher I, you will partner with a cross-functional team to develop AI-powered products, build AI foundation models, and conduct high-impact applied research in machine learning.