Top Tech Jobs & Startup Jobs

Supports NVIDIA’s Worldwide Field Organization by partnering with senior leaders on HR strategy, organizational design, workforce planning, talent management, performance management, compensation, employee relations, engagement, and leadership development. Advises managers and employees, analyzes workforce metrics, leads annual talent processes, and develops people solutions in a global, matrixed environment.

Advise on privacy law and data protection, review vendor contracts and DPAs, support third-party data sharing and transfer risk assessments, develop privacy review processes and playbooks, counsel business partners on privacy issues, monitor U.S. and international regulations, and assist with data governance guidelines and training.

Develop and productize deep learning perception systems for autonomous driving, including traffic signal, sign, road marking, and construction object understanding. Lead end-to-end model development, data-driven improvement, simulation, augmentation, and deployment to embedded platforms. Optimize solutions for accuracy, safety, latency, robustness, and regional generalization while collaborating with data-labeling teams and contributing technical leadership.

Develop and integrate autonomous vehicle control software for trajectory tracking, model predictive control, state estimation, vehicle dynamics, and safety-critical systems. Build embedded C/C++ modules, simulation models, testing and benchmarking tools, calibration workflows, and automated verification suites. Integrate control functionality across vehicle platforms and troubleshoot actuation issues while contributing to system architecture, redundancy, and failure analysis.

Lead hands-on storage software engineering for large-scale GPU clusters. Contribute to open-source parallel and distributed file systems, write and review production code, troubleshoot I/O, metadata, corruption, and recovery issues, validate performance and durability through scale testing, and establish configuration and operational standards. Collaborate with AI, SRE, networking, security, cloud, and storage teams while supporting high-performance storage across cloud, neocloud, and on-premises environments.

Support NVIDIA enterprise customers using GPU-accelerated platforms, triage hardware and AI/ML workload issues, collaborate with engineering teams, and drive cases through resolution. Develop support tools and products using AI, document customer interactions, and troubleshoot Linux-based multi-GPU systems, firmware, kernels, drivers, containers, and distributed workloads. The role also requires customer communication, technical analysis, and occasional weekend or holiday support.

Design and build distributed services, data pipelines, APIs, and integrations for GPU capacity planning, reservations, allocation, forecasting, and utilization. Establish unified capacity models across cloud providers and regions, automate operational workflows, improve observability and reliability, and resolve complex production issues. Lead technical design reviews, set engineering standards, mentor engineers, and collaborate cross-functionally on business-critical DGX Cloud infrastructure.

Lead cross-functional compiler software programs from concept to delivery, coordinating global teams, tracking risks and schedules, and improving development processes. Present status to executives, drive Agile and Waterfall projects, resolve technical/resource conflicts, and implement process and tool automation to ensure timely product releases.

Lead operations for a global events organization: manage multi-million dollar budgets, build operational processes/tools and reporting, evaluate event tech stack, coordinate cross-functional planning, remove bottlenecks, and drive high-priority initiatives to improve portfolio performance and scalability.

Lead customer solution architecture and application engineering for NVIDIA embedded and automotive systems. Collaborate with hardware, firmware, software, sensor validation, and AI teams to define system requirements, integrate SoC solutions, optimize performance, power, thermal, and mechanical characteristics, and support customers from product introduction through mass production. Lead partner enablement and multidisciplinary technical teams while developing architectures, roadmaps, documentation, and validation plans.