Top Tech Jobs & Startup Jobs

Lead and scale an engineering team building GPU-accelerated deep learning inference frameworks. Drive strategy and roadmap, partner with compiler/libraries/research teams, oversee performance tuning and multi-GPU optimizations, mentor engineers, and deliver production-ready inference pipelines for LLM, multimodal, and generative AI across datacenter and edge platforms.

Design, develop, and optimize system software and firmware for SoC-based O-RAN infrastructure. Implement power-management policies (DVFS, clock/power gating, thermal control), analyze RU/DU workloads, build performance and power models, create measurement and test tooling, validate on simulation/emulation and silicon, and influence SoC and platform architectures for 5G/6G deployments.

Lead DFT methodology and IP design for SoC products, owning fuse controller architecture, RTL development, verification, and full-chip test plans. Collaborate with cross-functional teams for integration, support post-silicon bring-up and ATE validation, debug failures, and mentor junior engineers.

Design and implement CUDA/C++ libraries to accelerate Apache Spark DataFrame and I/O operations, collaborate on distributed multi-node GPU solutions, contribute to open-source projects (RAPIDS, CCCL, UCX), and drive testing, CI, and cross-platform optimization for enterprise deployments.

Partner with architecture and design teams to plan and execute functional and performance verification for GPU memory subsystem IP. Develop testbenches, BFMs, monitors and regressions, close coverage, enable FPGA/software testing, and support post-silicon verification and debug to sign off RTL.

Lead developer relations and research partnerships in 6G and AI-native RAN. Conduct simulations, design and code AI/ML and LLM algorithms for RAN, publish papers and IP, engage 3GPP and AI-RAN bodies, and collaborate with cross-functional teams to drive accelerated-computing solutions.

Lead segment sales for RTX PRO Blackwell Server Edition, build pipeline and partner ecosystem, drive OEM/channel execution and GTM strategy, manage reporting and forecasting, and enable complex sales engagements for enterprise AI inference and GPU workloads.

The Senior Manager, Robotics Quality Assurance will lead test engineering strategy, automation development, and validate models for robotics products, ensuring quality across hardware and software.

The role involves developing and implementing features for the CUDA driver and collaborating on solutions for NVIDIA's compute platform, requiring strong coding and design skills.

The role involves developing automated tests and tools for NVIDIA software, focusing on improving quality and efficiency through Python programming and AI-assisted development tools.