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

Lead engineers building and operating DGX Cloud infrastructure across NVIDIA Cloud Partner and on-prem environments. Drive cluster operations, Kubernetes operability, automation, GitOps, observability, and incident response. Define roadmap, staffing, and operational ownership while partnering with platform, storage, networking, security, and TPM teams. Mentor engineers and foster a healthy on-call and incident review culture focused on durable fixes and operational excellence.

Build and operate massively distributed, scalable GPU cluster platforms (DGX Cloud) to monitor, diagnose, and remediate GPU performance issues. Ensure reliable, high-performance production AI clusters, evaluate failures, improve services via incident management, and collaborate across teams to automate cluster operations and scheduling.

Design and deploy LLM-powered validation pipelines and AI integrations for silicon design toolchains. Collaborate across teams to identify AI opportunities, build productionized agentic workflows, evaluate emerging AI tech, and measure impact with data systems to improve validation, characterization, and automation of chip bring-up and verification.

Architect, build, and deploy LLM-powered AI systems and automation to accelerate post-silicon validation and toolchain workflows; integrate AI across engineering teams, evaluate emerging frameworks, measure impact, and operationalize solutions from prototype to production while supporting silicon bring-up and lab debug.

Lead architecture and delivery of an ML infrastructure efficiency platform across silicon co-design teams. Define platform contracts, onboarding, orchestration, auth, observability, storage/caching, and SLA enforcement. Own production operation, security, reliability, and performance while mentoring engineers and driving cross-team technical decisions.

The role involves mentoring on Gen AI solutions, developing POCs, educating customers on technologies, and collaborating with various teams for product development.

Build and maintain automation flows and methodologies for VLSI interposer design. Develop tools and applications (Python/C++) to construct, analyze, and validate interposer designs, improve designer workflows, and integrate AI/ML-assisted techniques into EDA environments.

Design and implement production-grade VLSI/EDA tools and methodologies for multi-die package design. Build flows, applications, and automation to construct, analyze, validate, and optimize package designs to accelerate tape-out and scale engineering teams.

Build and operate scalable backend services and data platform integrations for customer profiles, consent, personalization, campaign operations, and marketing intelligence. Design APIs, service integrations, and reusable platform capabilities; modernize database and identity systems; ensure reliability with observability, automation, and incident prevention; partner with cross-functional teams to translate business needs into production-ready solutions using AI-assisted engineering responsibly.

Lead design and development of infrastructure, automation frameworks, and internal developer tools. Build scalable services, APIs, dashboards, workflow engines, and LLM-powered workflows integrated with CI/CD, source control, test infrastructure, and observability. Define architecture and reliability practices, mentor engineers, review designs, and provide technical leadership for automation and tooling projects.