Top AI & Machine Learning Jobs in San Francisco, CA

Lead data science engagements with customers to acquire and prepare data, build and evaluate scalable models, implement production-ready solutions, and define business and solution strategy while collaborating with engineers and product teams.

Lead data science strategy across complex customer engagements: frame business problems, define modeling and data readiness standards, produce reusable operational ML patterns, provide hands-on coding and MLOps expertise, mentor teams, and influence executive stakeholders to drive measurable business impact and responsible AI practices.

Design, implement, and optimize distributed training infrastructure and telemetry for large-scale GPU clusters. Profile, benchmark, and debug performance across compute, memory, networking, and storage. Improve fleet-wide efficiency through tooling, architectural changes, and collaboration with ML researchers and hardware teams to support next-generation accelerators and large-scale generative AI workloads.

Lead design and implementation of ONNX, ONNX Runtime, and on-device inference (Foundry Local). Provide technical leadership, write design documents, mentor engineers, own cross-product dependencies and release plans, act as DRI and on-call for reliability, and drive performance, observability, and operational consistency at scale.

Customer-facing Cloud Solution Architect who designs and deploys secure, scalable, AI-ready data platforms on Azure. Leads architecture sessions, proofs-of-concept, and production deployments, ensuring performance, resiliency, and security. Drives adoption, identifies expansion opportunities, enables partners, contributes to IP and technical readiness, and represents Microsoft in technical communities and events.

Lead data acquisition, cleaning, modeling, and evaluation for customer-facing cloud AI solutions. Coach engineers on best practices, build operational scalable models, research industry trends, and define solution strategy with cross-functional teams.

Lead technical strategy with priority partners across ASEAN to build repeatable Microsoft Cloud and AI services. Translate business priorities into technical roadmaps, run innovation workshops, guide architecture/design, validate offers, enable partner readiness, and drive co-sell execution to convert technical work into measurable revenue and consumption.

Lead end-to-end data science and AI engagements: design, build, deploy and evaluate models; mentor teams; engage stakeholders; drive Responsible AI adoption and measurable business impact using Microsoft technologies.

Lead technical strategy and execution with strategic partners across ASEAN to build repeatable Microsoft Cloud and Data & AI offerings. Guide architecture, run innovation workshops, enable partner specializations, validate offers, and drive co-sell execution to convert technical work into measurable revenue and consumption.

Lead design and implementation of vector search and semantic retrieval features, translate research into product, own architecture decisions, mentor engineers, improve code quality and test strategy, collaborate with partner teams for end-to-end scalability, performance, and release planning.