Top Tech Jobs & Startup Jobs

Develop production-grade multimodal AI systems for L3/L4 autonomous vehicles. Build sensor-fusion and spatiotemporal world models combining camera, LiDAR, radar, navigation, and vehicle-state data. Create multitask models for road understanding, occupancy, perception, prediction, and planning; develop scalable training and evaluation pipelines; investigate foundation-model approaches; optimize models for real-time NVIDIA hardware; and collaborate across AV engineering teams to deploy robust systems.

Lead the strategy definition and implementation for NVIDIA Infrastructure Specialists professional services programs. Coordinate field and headquarters teams, manage timelines, deliverables, resources, risks, objectives, and KPIs, and improve operational workflows and reporting infrastructure. Facilitate cross-functional communication and maintain accurate program records using operational systems. The role supports large-scale AI Factory deployments and requires extensive program management experience in technical operations or professional services.

Leads OEM sales growth for NVIDIA technologies through partner relationships, cross-functional team leadership, go-to-market strategy, C-suite engagement, strategic opportunity development, product roadmap coordination, partner compliance, server design qualification, marketing alignment, and forecasting. The role focuses on expanding NVIDIA’s partner portfolio and achieving revenue and business objectives across enterprise data center markets.

Own the roadmap and delivery of AI infrastructure resilience platform features, including telemetry, health checks, attribution, observability APIs, and deployment experiences. Translate developer needs into product strategy, collaborate with engineering on architecture and execution, engage open-source contributors through GitHub, and align product, marketing, field, and engineering teams. The role requires deep technical expertise in AI infrastructure, Kubernetes, developer platforms, or related systems, plus extensive product management or engineering experience.

The Solutions Architect will evaluate server and computing solutions, coordinate qualification and certification, and support OEM relationships. Responsibilities include analyzing full-system architectures, troubleshooting schematics, diagnostics, test results, thermal and electrical data, and improving CPUs, GPUs, memory, storage, power, cooling, and interconnects. The role manages multiple technical cases, translates complex findings into recommendations, and supports AI infrastructure projects from the Round Rock area with required travel.

Develop embedded networking software for NVIDIA Spectrum-X products. Responsibilities include debugging complex networking issues, building diagnostic tools and processes, collaborating with global engineering and product teams, and engaging directly with customers to address technical requirements. The role requires strong C and Python programming on Linux, embedded networking experience, analytical problem-solving, leadership in AI-native software development, and effective communication.

Serve as the senior technical contact for OEM Federal deployments of NVIDIA GPU-accelerated platforms. Own customer issues end to end, including troubleshooting, failure analysis, RMA procedures, root-cause investigation, and coordination with OEM support and NVIDIA engineering. Support secure Federal environments such as FedRAMP, IL5/IL6, and air-gapped SCIF facilities while maintaining sanitization and chain-of-custody requirements. Analyze multi-GPU systems, firmware, operating systems, networking, storage, and distributed workloads, with up to 35% travel.

Design and build intelligent compiler systems, compiler-oriented agents, code transformation workflows, and numerical verification infrastructure. Develop systems for low-level IR reasoning, code generation, optimization, differential testing, regression detection, and correctness validation across GPU-centric workloads. Collaborate with compiler, CUDA, runtime, library, and hardware teams to integrate capabilities into NVIDIA products while optimizing performance, scalability, and numerical correctness.

Build and operate production agentic AI systems for executive IT insights. Develop conversational analytics agents, connect governed enterprise data through MCP, create Slack and Microsoft Teams delivery integrations, and implement validation layers that prevent hallucinated or inaccurate recommendations. Translate data into actionable portfolio and operational guidance for CIO and VP audiences while collaborating with data warehousing, AI engineering, and reporting teams.

The Senior Firmware Engineer will develop, architect, and debug firmware for GPUs, focusing on communication, peripheral management, and high-reliability systems.