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

As a senior software engineer at NVIDIA, you will design and build tools for performance analysis of AI workloads, lead automation efforts, and enhance workflows for engineers.

The Senior Site Reliability Engineer will enhance service reliability, manage production systems, automate processes, lead incident responses, and optimize system performance at NVIDIA's GeForce NOW.

Lead applied research to improve human-centric video/world foundation models: design and validate architectures, optimize training and inference, develop benchmarks, and productionize checkpoints and integrations to boost fidelity, temporal stability, and sim-to-real generalization.

Design and build real-time, physics-informed AI models and synthetic data pipelines for quantum calibration and decoding. Develop surrogate models and GPU-accelerated implementations, apply reinforcement and online learning for calibration policies, co-design low-latency calibration-decoding systems, and collaborate across engineering and research to enable fault-tolerant quantum hardware.

The role involves designing GPU memory systems, developing performance models using AI, and optimizing architecture based on analyses of benchmarks and workloads, while collaborating with engineering teams.

Design, implement, and lead Identity Governance solutions (SailPoint) across cloud and on-prem infrastructure. Integrate IAM with CyberArk, HashiCorp Vault, and Azure; apply agentic AI to automate workflows; mentor engineers; drive Zero Trust, compliance (SOX), and SDLC/DevSecOps integration for identity tooling and operations.

Lead design and delivery of SAP IBP planning solutions (supply, demand, optimization, fulfillment). Build prototypes, integrate data, perform testing, support and debug IBP systems, and collaborate with cross-functional teams to improve supply chain profitability and scalability.

As a Senior AI Solutions Architect, you'll drive the use of NVIDIA AI solutions, support developers, and analyze application architectures to enhance performance.

The role involves integrating AI supercomputing systems into datacenters, collaborating with engineering teams, and producing documentation for processes related to datacenter integration and fit-out.

Design, build, and operate scalable AI inference infrastructure across cloud and on-prem. Own Kubernetes deployments, CI/CD pipelines, IaC, observability, incident response, and infrastructure security. Collaborate with ML framework and compiler teams to streamline end-to-end deployment and reduce operational toil.