Top Tech Jobs & Startup Jobs

Supports security architecture, certification, compliance, threat modeling, and secure design reviews for NVIDIA SoCs and GPUs. Collaborates with hardware, firmware, software, verification, and product teams on secure boot, cryptography, hardware roots of trust, and platform security. Builds AI-assisted tools for architecture reviews, requirements analysis, evidence tracking, and security workflows. The role is designed for a new college graduate with foundational knowledge in computer architecture, embedded systems, cryptography, or cybersecurity.

Leads architecture and development of NVIDIA’s network visibility platform, integrating topology, configuration, telemetry, active measurement, change intelligence, and self-service tools. Builds authoritative network models, defines observability and measurement strategies, establishes data contracts and quality standards, and delivers health, path, and blast-radius insights. Drives cross-functional roadmaps, build-versus-buy decisions, operational tradeoffs, and technical mentorship across large-scale infrastructure systems.

Verify NVIDIA GPU ASIC designs across architecture, microarchitecture, golden models, and implementations. Develop verification scopes and infrastructure using UVM or equivalent methodologies, random stimulus, functional coverage, and assertions. Build unit- and system-level testbench environments, debug issues with simulation and analysis tools, and collaborate with architects, designers, and pre- and post-silicon verification teams.

Conduct performance, image quality, and power testing across NVIDIA GPUs and AI, LLM, and 3D applications. Develop Python automation tools, maintain and debug hardware, analyze competitive and internal benchmark data, identify performance bottlenecks, validate test results, and create reports that guide product initiatives and business decisions.

Lead technical collaborations with software partners and developers focused on Generative AI, autonomous vehicles, simulation, NVIDIA Omniverse, and Cosmos platforms. Advise on architecture, code, integrations, reference solutions, enablement resources, and technical go-to-market activities. Provide partner feedback to product and engineering teams, support launches, and guide startups through onboarding. The role requires deep AI, autonomous vehicle, GenAI, cloud deployment, DevOps, and developer advocacy expertise.

Own the product vision, architecture, roadmap, and delivery of NVIDIA’s enterprise data observability platform. Build reusable data quality, governance, lineage, and AI-agent frameworks supporting supply chain domains. Design LLM inference and agentic capabilities for anomaly detection and self-healing pipelines, establish data ownership and governance artifacts, and coordinate engineering, data, business, and executive stakeholders through deployment and adoption.

Develops and delivers manufacturing, test, failure-analysis, and recovery processes for complex NVIDIA datacenter servers and assemblies. The role coordinates with hardware, firmware, software, manufacturing, and quality teams; supports prototype and validation builds; analyzes throughput, yield, and failure data; develops assembly and test documentation; debugs server platforms; and drives process improvements, product quality, and cost optimization.

Build scalable financial data infrastructure for payment, invoicing, ledger, and transaction systems. Architect Kafka-based event-driven pipelines with transactional integrity, develop data models, automate ETL/ELT processes, and improve data quality and reliability. Design REST APIs and cloud services using PostgreSQL, Databricks, dbt, and lakehouse technologies. Collaborate across teams to automate financial operations and create resilient, self-monitoring distributed systems.

Develop and maintain GPU performance foundation libraries and test frameworks for Nsight tools. Implement GPU assembly tests, use emulators/simulators to validate instruction events, and document data workflows. Collaborate with hardware architecture teams to enable performance analysis and optimization of GPU-accelerated applications.

Leads NVIDIA’s embedded GPU and long-life board product portfolio, managing customer relationships, design wins, pricing, supply commitments, lifecycle planning, and product roadmaps. The role coordinates Engineering, Sales, Finance, Operations, campaign teams, and partners through product introduction, launch, long-life support, and end-of-life transitions. It requires advanced hardware and software platform experience, commercial acumen, lifecycle management expertise, strong communication, and at least 25% travel.