Top Tech Jobs & Startup Jobs in NYC, NY

Provide technical support to NVIDIA Enterprise customers by triaging and resolving issues, working with engineering on reproductions/logs, applying AI/ML and agentic AI to build support tools and products, documenting interactions and knowledge, and owning cases to resolution (occasional weekend/holiday support).

Provide advanced support and root-cause analysis for NVIDIA networking technologies in AI clusters. Reproduce and resolve customer issues, develop fixes and tools, analyze performance/tuning for high-performance lossless networks, collaborate with R&D and customers, and occasionally support outside regular hours.

Research and implement GPU-acceleration techniques for high-performance databases and ETL. Analyze and optimize data-intensive workloads, collaborate with hardware, systems, and research teams to influence next-generation architectures and programming models, and publish/share findings with customers and the community.

Research and develop techniques to accelerate large-scale applications on advanced CPU platforms. Analyze and optimize database and analytics workloads for CPU performance, collaborate with internal and external experts, publish findings, and influence next-generation hardware/software design.

Lead a team of performance engineers to optimize complex workloads on NVIDIA's CPUs and GPUs, driving technical excellence and innovation while mentoring team members and collaborating with cross-functional partners.

Provide advanced technical support for NVIDIA InfiniBand, NVLink and GPU-based HPC/AI infrastructure. Troubleshoot installations, networking and interoperability issues on multi-distro Linux, reproduce and resolve customer problems, use packet analysis and cluster tools, and collaborate with engineering, marketing, and support teams to improve processes and documentation.

The role involves designing and developing VLSI CAD software, collaborating in agile practices, and advancing design tools for chip development.

This role involves researching and optimizing applications for NVIDIA's computing platform, collaborating with customers and internal teams to enhance performance and design next-generation software and hardware.

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.

Develop and optimize GPU-accelerated algorithms for quantum circuit simulations, collaborating with various teams, and leading technical efforts.