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

Develop innovative physical design methodologies for GPUs and SOCs, focusing on PPA improvements and collaboration across multiple teams. Use AI/ML to enhance design efficiency.

Design, deploy, maintain, tune, and secure enterprise Linux environments supporting high-performance EDA compute farms. Lead infrastructure-as-code automation, configuration management, continuous deployment, and tooling development using Python, Bash, or Go. Manage LDAP/SSSD naming services, NFS and Autofs storage, virtualization, container infrastructure, registries, networking, and infrastructure telemetry. Support highly available, scalable systems and potentially integrate cloud platforms, CI/CD pipelines, EDA toolchains, and HPC clusters.

Develop Rust-to-GPU compiler pipelines, custom intermediate representations, optimizers, and ahead-of-time, just-in-time, and link-time compilation tooling for NVIDIA GPUs. Design Rust-based safety abstractions across GPU execution boundaries and expose low-level CUDA hardware features. Responsibilities include compiler architecture, GPU code generation, debugging, profiling, benchmarking, and independently driving complex engineering initiatives from research through production.

Design, deploy, operate, and automate reliable large-scale EDA infrastructure services on NVIDIA hardware. Build tools that reduce manual work, support distributed private and public cloud systems, define service-level objectives, improve observability, and participate in incident response and on-call rotations. The role also provides systems-design guidance to peer teams and may involve Kubernetes, OpenStack, Docker, Slurm, multi-cloud infrastructure, networking, storage, and GPU-based systems.

Leads a distributed team securing NVIDIA DGX Cloud’s large-scale GPU infrastructure. Responsibilities include hiring and developing engineers, setting strategy for security control planes and foundational services, delivering measurable risk reduction, maintaining engineering standards, communicating security risks to executives, and collaborating with platform, SRE, networking, and security teams. The role requires strong engineering management, infrastructure or security expertise, cloud-native fluency, and influence across partner organizations.

Builds developer and customer relationships across the Jetson ecosystem, guides partners through embedded Linux and Jetson software integration, promotes NVIDIA AI libraries and edge AI capabilities, supports production deployments, and communicates developer feedback to engineering and product teams to shape platform roadmaps, reference designs, positioning, and adoption.

Design and implement GPU compiler components, optimize compiler performance, solve graphics and parallel-computing compilation problems, collaborate with GPU driver and architecture teams, contribute to LLVM and DXC open-source projects, and help define SPIR-V extensions and standards.

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.

Design and operate large-scale infrastructure supporting GPU- and CPU-based EDA workloads. Build automation for provisioning, configuration, deployment, lifecycle management, monitoring, health remediation, cluster enrollment, and recovery across Linux compute fleets. Integrate services with schedulers, infrastructure systems, and observability platforms. Participate in incident response, root-cause analysis, capacity planning, and reliability improvements while collaborating with EDA, networking, storage, and hardware teams.

Owns customer relationships and revenue growth for NVIDIA’s supercomputing, HPC, and AI products across federal government and academic accounts. Responsibilities include demand creation, co-selling, forecasting, strategic account development, partner collaboration, go-to-market execution, customer education, and communicating customer-driven product strategy. The role focuses heavily on DOE labs, federal purchasing processes, long-term technology partnerships, and ecosystem expansion, with travel up to 50%.