Top Tech Jobs & Startup Jobs

Develop and optimize reinforcement learning algorithms and infrastructure for large language and multimodal models. Enable open-source model support in NVIDIA RL and post-training frameworks, collaborate with research and engineering teams, guide customers integrating NVIDIA technologies, and maintain reusable toolchains, experiment workflows, and documentation. The role requires strong PyTorch, distributed training, and experimentation skills, with preferred experience in RLHF, GRPO, DPO, GPU optimization, agentic AI, and multimodal reinforcement learning.

Serve as NVIDIA’s technical liaison with OEM server manufacturers, driving adoption of Arm-based data center CPUs. Architect and validate enterprise and AI server platforms, guide x86-to-Arm workload migration, tune performance, resolve CPU-memory-network integration issues, and collaborate with engineering, ISV, and open-source communities. Create technical content and present to technical and executive audiences. Support firmware, Linux, bootloader, hardware validation, benchmarking, and competitive performance analysis.

Oversee planning and execution of VLSI programs in Networking, ensuring alignment with corporate goals, while managing cross-functional teams and addressing risks.

Design and deploy AI applications for telecommunications networks, focusing on generative models and infrastructure improvements, while providing technical guidance and building enterprise solutions.

Designs and develops physical implementation for high-speed networking chips, optimizing power, area, and performance. Responsibilities include RTL-to-GDSII flows, synthesis, power and clock distribution, place and route, timing closure, power and noise analysis, physical verification, and resolving timing and congestion challenges. The engineer also contributes to flow development and integration while applying LVS and DRC verification methodologies using industry-standard EDA tools such as Synopsys and Cadence.

Perform physical design for chip blocks and top-level designs from RTL through GDS. Responsibilities include synthesis, power and clock distribution, place and route, timing closure, power and noise analysis, physical verification, and resolving timing and congestion challenges. The engineer will contribute to flow development and serve as the technical leader and focal point for partition- or unit-level physical design.

Develop and validate digital test content (ATPG, LBIST, MBIST) for network ICs; run simulation/emulation/silicon validation flows, analyze failures, debug patterns, collaborate with DFT and test teams, support tester bring-up and pattern integration, and improve coverage and pattern generation efficiency to support yield and product quality.

Develop embedded real-time systems software for autonomous vehicle safety services. Optimize solutions for performance and compliance while collaborating with multifaceted teams to integrate technologies into NVIDIA's self-driving platform.

This role involves developing high-performance software for autonomous vehicles, focusing on sensor drivers, data processing, and vehicle interface integration, while adhering to quality standards.

Develop system requirements, performance budgets, test strategies, metrics, and verification processes for L3/L4 autonomous driving products. Analyze safety-critical systems, datasets, and software architectures while coordinating vehicle and component testing. Partner with engineering, safety, validation, analytics, and product teams to ensure functional and safety compliance. Apply SOTIF, ISO 26262, architectural trade-off analysis, and validation strategies for deep learning and modular autonomous-driving systems.