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

Own the production serving path for multimodal AI models, including Rust inference runtime nodes, GPU kernels, routing, batching, streaming, quantization, observability, and low-latency optimization. Productionize research checkpoints and improve GPU utilization, numerical precision, latency, and cost while collaborating closely with researchers.

Build and operate backend platform capabilities including REST APIs, SDKs, agent runtimes, multi-tenant ingestion, and GPU job orchestration. Design resilient services for cloud, customer VPC, on-premises, and edge deployments. Own observability, reliability, SLOs, debugging, and on-call operations while translating AI research into production infrastructure. Senior engineers also drive architecture and engineering standards.

Lead enterprise customer programs from initial scope through pilot, production, and expansion. Align customer goals with engineering execution through milestones, dependencies, decisions, and success criteria. Resolve technical risks, cross-functional blockers, and tradeoffs while coordinating Solutions, Research, Product, and Engineering teams. The role requires technical fluency in AI/ML, data, cloud, APIs, or complex software systems, with emphasis on delivering ambiguous, data-centric products in real-world environments.

Design, train, and interpret foundation models for multimodal sensor data. Develop representation learning, multimodal alignment, self-supervised learning, and model adaptation methods. Diagnose limitations and failure modes, design experiments, and collaborate with engineering and product teams to translate research into production systems.

Own full enterprise sales cycle for physical AI platform: drive net-new business and expansions, manage complex seven-figure deals, build executive relationships, inform GTM/product strategy, meet quarterly revenue targets, and maintain CRM/account plans.

The role involves building and improving multimodal foundation models that integrate various types of data for real-world applications, requiring strong research capabilities and deployment experience.