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

Lead the technical narrative and content strategy for NVIDIA DSX, an AI factory platform spanning facilities, power and cooling, compute, networking, storage, software, orchestration, simulation, models, and workloads. Develop reference architectures, whitepapers, guides, demos, workshops, training, videos, and launch assets. Coordinate cross-functional teams and partners, lead flagship demos, identify ecosystem opportunities, influence roadmap and positioning, mentor contributors, and measure content adoption.

Lead architecture for cloud networking and security solutions involving DPUs and NICs. Design end-to-end systems from application to hardware, define architecture specifications, evaluate technologies, develop proof-of-concept prototypes, and collaborate with global software, hardware, product, engineering, and customer teams. The role requires strong C and Python development, Linux, networking protocols, cloud technologies, and systems architecture expertise.

Design and optimize custom SRAM circuits for performance, area, power, functionality, and robustness across advanced semiconductor processes. Collaborate with mask designers on dense pitch-matched layouts, verify electrical integrity, and improve design automation, data collection, and analysis flows. The role supports custom memory development for NVIDIA processing chips and requires strong SRAM design expertise, circuit design experience, and familiarity with semiconductor design and verification tools.

Own and optimize IBM Spectrum LSF scheduling across 15–25 federated cells. Diagnose scheduler latency, MultiCluster forwarding and cross-cluster contention, design scalable cell topology, and encode scheduler policy through infrastructure as code. Partner with CAD and methodology teams on large-scale EDA workloads, license constraints, and tape-out bursts. Requires deep LSF internals expertise, production MultiCluster experience, strong Linux fundamentals, and Python, Perl, and shell scripting skills.

Designs and deploys large-scale AI and HPC GPU cloud infrastructure for NVIDIA Cloud Partners. Serves as the primary technical advisor across solution design, development, integration, production, debugging, and customer adoption. Builds proof-of-concepts, integrates AI software stacks, libraries, frameworks, and models, and delivers technical presentations and workshops. Partners with engineering, product, sales, and business teams to secure opportunities, guide product strategy, and support complex customer engagements throughout the lifecycle.

Develop HPC and AI software workflows for experimental data processing, imaging, plasma, high-energy physics, and materials simulations. Profile applications, benchmark performance, identify bottlenecks, and advise collaborators and product teams. Build tutorial examples, translate research into software tools, and represent NVIDIA at scientific conferences and industry events.

Design and develop RTOS and hypervisor features, bring up and optimize software stacks on NVIDIA Tegra SoCs, and debug system-level issues across hardware, firmware, RTOS, and virtualization layers. The role develops high-integrity automotive software using safety and security practices, while leading cross-team technical initiatives and coordinating execution. Candidates need strong C/C++ systems programming, embedded software expertise, operating-system knowledge, hardware-assisted virtualization experience, and at least eight years of experience.

Build and operate AI infrastructure systems, including telemetry pipelines, observability dashboards, incident-management automation, hardware and software catalogs, service ownership data models, and self-service discovery tools. Lead cross-functional infrastructure initiatives and develop AI-assisted operational tooling. The role requires production software and infrastructure expertise, programming experience, and the ability to improve reliability, visibility, incident response, and operational efficiency across NVIDIA GPU cloud environments.

Build and lead development of NVIDIA’s open-source NeMo Core Platform for executing, evaluating, deploying, and optimizing agentic AI systems across local, Docker, Kubernetes, Slurm, on-premises, and air-gapped environments. Design platform APIs, plugins, SDKs, job orchestration, authentication, RBAC, observability, testing, and reliability features. Provide technical leadership through architecture and code reviews, mentoring, and ownership of complex cross-component problems.

Designs, deploys, maintains, and tunes large-scale HPC and AI clusters. Responsibilities include workload scheduling, infrastructure automation, CI/CD pipelines, monitoring, logging, alerting, storage and networking deployment, bottom-up troubleshooting, methodology documentation, and R&D support. The engineer works across hardware, operating systems, GPU computing, virtualization, cloud platforms, and software stacks to deliver performant, reliable self-service infrastructure.