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

Leads hardware security architecture and long-term security roadmaps for NVIDIA SoCs and GPUs. Designs mitigations for physical attacks, develops threat models for advanced packaging and photonics, reviews architecture and verification specifications, and evaluates AI-assisted vulnerability discovery. Collaborates with internal teams, customers, partners, standards bodies, and industry organizations to address security risks, supply-chain threats, hardware Trojans, fault injection, and side-channel attacks.

Develop and productize autonomous-driving perception software. Responsibilities include full SDLC execution, writing and testing C++ and Python code, integrating perception components, creating verification plans, deploying deep-learning models to embedded platforms, debugging systems, and evaluating performance with real and synthetic data.

Supports NVIDIA’s NALA Enterprise Sales organization through resource and headcount planning, territory and account performance analysis, target allocation, sales reviews, dashboard development, Salesforce governance, and executive reporting. The role coordinates cross-functional operational processes, improves data visibility, standardizes workflows, supports Zoom onboarding and adoption, and translates business data into actionable insights for sales leadership.

Leads production test design for NVIDIA networking platforms, including NICs, SmartNICs, DPUs, NVLink systems, and Ethernet switches. Develops test architectures, strategies, coverage, diagnostics, and software solutions while coordinating technical decisions across engineering, operations, security, and manufacturing teams. Partners with contract manufacturers and global teams to deploy test plans, reuse shared capabilities, and align production testing with platform development and manufacturing requirements.

Develop and productize machine learning prediction systems for autonomous driving. Responsibilities include designing end-to-end prediction solutions, researching deep learning models, supporting diverse driving environments, prioritizing data collection and labeling, using simulation and augmentation, and meeting safety, latency, and software robustness requirements. The role also involves collaboration with data teams and deployment of real-time ML solutions to embedded platforms.

Develop GPU code generation and compiler optimizations for TensorRT to improve generative AI inference performance. Responsibilities include operator fusion, scheduling, specialization, profiling, debugging, numerical validation, and performance analysis. The role requires C++ software development and GPU architecture expertise, with collaboration across hardware, compiler, kernel, and deep learning teams. Preferred experience includes CUDA, MLIR, GPU kernels, Tensor Core optimization, inference frameworks, and low-level NVIDIA performance tools.

Develop and optimize NVIDIA’s proprietary C++ GPU compiler backend. Responsibilities include designing compiler passes, improving code generation and machine instruction performance, supporting GPU architectures, and collaborating with compiler, hardware, and application teams. The role requires strong C++ and compiler code-generation expertise, with preferred experience in LLVM, instruction scheduling, register allocation, CUDA, DirectX, OpenGL, and Vulkan.

Design and guide security architecture for NVIDIA networking firmware and embedded subsystems. Responsibilities include threat modeling, analyzing firmware and hardware interactions, defining lifecycle security features, translating threats into requirements, partnering with hardware architects, and driving secure firmware development practices such as memory-safe C, static analysis, and fuzzing. The role requires expertise in firmware security, authorization models, cryptography, secure boot, attestation, and embedded systems.

Drive technical engagements for NVIDIA’s on-premises AI Factory solutions. Advise partners, OEMs, and enterprise customers; design and validate scalable architectures; support deployments and troubleshooting; enable adoption of NVIDIA platforms; and communicate customer needs to engineering and product teams. The role requires hands-on expertise across AI infrastructure, hardware, firmware, operating systems, cluster management, workload orchestration, and system integration.

Build and operate security controls, telemetry, detections, and enforcement for NVIDIA’s large-scale EDA compute, storage, and networking infrastructure across on-premises and multi-cloud environments. Investigate threats, respond to incidents, automate secure configurations and compliance evidence, threat-model infrastructure, and manage security technology lifecycles. The role requires hands-on Linux, networking, programming, infrastructure security, and collaboration with infrastructure and security teams.