Top Tech Jobs & Startup Jobs

Design and develop software validation frameworks for SOC systems, improve software efficiency, and conduct debugging for complex system failures while collaborating cross-functionally.

Lead NVIDIA's storage strategy for AI Cloud, focusing on high-performance storage solutions for critical workloads, mentoring engineers, and influencing technical direction across teams and external partners.

Lead and own RMA and failure analysis for NVIDIA AI/ML products. Conduct and lead debug/root-cause analysis, scale FA capabilities, create 8D-style reports, analyze quality/RMA data, monitor hardware reliability metrics, manage FA operations at CMs, and oversee new-product FA setup.

The role involves driving physical design from netlist to GDS, working on timing closure, physical verification, and collaborating with mixed signal teams. Candidates should have experience in Synopsys or Cadence tools and physical design.

Define and design GPU and SoC-based products, guide design engineers, balance cost and performance, and manage project timelines.

Design and implement high-speed digital front-end and back-end for DSPs and silicon photonics IPs: define micro-architecture, calibration algorithms, translate to RTL/firmware, create synthesis constraints, drive timing closure, evaluate PPA trade-offs, and lead post-silicon bring-up, testing, characterization, and cross-functional production handoff.

The Senior Network Reliability Engineer will support cloud and datacenter networks, manage incidents, engage with vendors, and drive operational improvements.

Lead post-silicon bring-up and productization from first power-on through production ramp. Drive cross-functional execution for debug, validation, characterization, reliability qualification, and production readiness while establishing operating models, metrics, and closure plans for high-risk silicon issues.

Lead positioning, messaging, and launches for unstructured data processing and decision optimization products. Drive technical content, executive keynotes, community outreach (live-streams, hackathons), ecosystem analysis, and practitioner engagement to increase adoption of NVIDIA software and hardware platforms.

Lead and implement end-to-end, AI-enhanced employee experiences across web and mobile. Architect scalable services and UIs, embed LLM/vector-search and recommendation systems, integrate third-party HRIS and collaboration platforms, champion modern front-end patterns and cloud-native back-end practices, ensure observability and reliability, and mentor engineers while upholding security, privacy, and accessibility standards.