Top Tech Jobs & Startup Jobs

The Senior Formal Verification Engineer will verify ASICs using formal verification methods, ensuring correctness and collaborating with architects and designers across projects.

Develop and optimize on-device AI capabilities for NVIDIA’s GeForce G-Assist. Evaluate Small Language Models for accuracy, robustness, conversational reliability, and contamination issues. Build multimodal and hybrid local-cloud architectures, optimize llama.cpp inference using C/C++, and integrate retrieval-augmented generation and agentic workflows involving planning and tool use. Collaborate with engineering and product teams to balance model performance, system reliability, and user experience.

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 HDCP security activities across SoC projects, including roadmap ownership, protocol implementation, compliance certification, and delivery. Develops secure firmware on RISC-V processors and integrates solutions across Linux and Android platforms. Drives production signing, rollback prevention, key provisioning, threat modeling, vulnerability remediation, and security compliance. Collaborates with hardware, boot firmware, validation, power management, and GPU display teams from architecture through product delivery.

Build and operate docs-as-code systems, CI/CD pipelines, content automation, and AI-ready knowledge infrastructure for simulation technology documentation. Develop tooling, templates, validators, RAG and agent workflows, and LLM-assisted content processes. Partner with documentation, engineering, product, security, and developer relations teams to improve information architecture, content quality, self-service, onboarding, support deflection, and AI answer accuracy.

Build and optimize CUDA kernels for molecular dynamics simulations, deliver GPU-accelerated math primitives, integrate them into major simulation engines, and develop CI/CD systems for performance testing across NVIDIA GPUs. Collaborate with applied scientists to productionize algorithms and support external partners. The role requires deep C/C++ and CUDA expertise, high-performance computing experience, familiarity with molecular dynamics, and experience developing scientific software or GPU APIs.

Build and integrate software for simulated and physical humanoid robots using NVIDIA robotics technologies. Develop end-to-end workflows for data collection, simulation, training, evaluation, and deployment of autonomous capabilities. Extend platforms to new robot embodiments, deploy learned policies, and resolve compute, latency, bandwidth, and software-hardware integration challenges. Collaborate internationally to deliver reliable robotic systems and agent-driven robotics interfaces.

Leads silicon product engineering for high-volume manufacturing, including system-level production diagnostics, test coverage, silicon bring-up, validation, debugging, yield optimization, and test flow development. Partners with hardware, software, platform, production, quality, and customer teams to improve manufacturability, test efficiency, cost, and product quality. Drives root-cause analysis, data analytics, production correlation, and manufacturing test strategy from planning through production ramp.

Provide technical mentorship to customers adopting NVIDIA’s GenAI stack, build and deploy agentic AI solutions, create demonstrations and proofs of concept, deliver technical workshops, develop industry collateral, and collaborate with engineering, product, and sales teams to secure design wins. The role focuses on optimizing and deploying large language models, leveraging GPU clusters, inference engines, cloud platforms, and AI development frameworks.

Lead complex technical programs for NVIDIA’s autonomous vehicle platform, driving software and hardware technologies from bring-up through production. Manage roadmaps, releases, schedules, risks, dependencies, quality, and cross-functional engineering teams across software, hardware, vehicle, systems, and validation. Improve development processes, coordinate automotive software releases, and communicate program status and decisions. The role requires strong technical knowledge, leadership, and experience delivering commercial software products in fast-paced environments.