Top Tech Jobs & Startup Jobs in NYC, NY

Lead architecture for cloud networking and security solutions involving DPUs and NICs. Design end-to-end systems from application to hardware, define architecture specifications, evaluate technologies, develop proof-of-concept prototypes, and collaborate with global software, hardware, product, engineering, and customer teams. The role requires strong C and Python development, Linux, networking protocols, cloud technologies, and systems architecture expertise.

Designs and deploys large-scale AI and HPC GPU cloud infrastructure for NVIDIA Cloud Partners. Serves as the primary technical advisor across solution design, development, integration, production, debugging, and customer adoption. Builds proof-of-concepts, integrates AI software stacks, libraries, frameworks, and models, and delivers technical presentations and workshops. Partners with engineering, product, sales, and business teams to secure opportunities, guide product strategy, and support complex customer engagements throughout the lifecycle.

Build and lead development of NVIDIA’s open-source NeMo Core Platform for executing, evaluating, deploying, and optimizing agentic AI systems across local, Docker, Kubernetes, Slurm, on-premises, and air-gapped environments. Design platform APIs, plugins, SDKs, job orchestration, authentication, RBAC, observability, testing, and reliability features. Provide technical leadership through architecture and code reviews, mentoring, and ownership of complex cross-component problems.

Lead NVIDIA’s RL post-training frameworks strategy and engineering ecosystem across distributed training, inference, rollout, evaluation, orchestration, and NVIDIA platforms. Build and manage globally distributed teams, prioritize upstream and internal investments, establish benchmarks and execution metrics, and drive reliable open-source integrations. Partner with research, product, hardware, CUDA, networking, and external communities to scale reinforcement learning workloads across GPUs and heterogeneous systems.

Design and implement LLM-first APIs and documentation for CUDA-X math libraries. Develop tools, metrics, and processes to improve AI-agent code generation and transform library APIs into LLM-friendly formats. Collaborate with stakeholders on LLM-enhanced releases while prototyping solutions for code-generation platforms. Requires expertise in LLMs, fine-tuning, reinforcement learning, RAG, MCP, agent tooling, composable API design, and technical documentation.

Design, develop, integrate, test, and productize perception software for autonomous driving systems. Responsibilities include implementing robust and reusable software components, deploying deep neural network models to embedded real-time platforms, developing verification plans, debugging systems, maintaining documentation, and analyzing real or synthetic benchmark data. The role requires close collaboration with perception engineers and researchers throughout the software development lifecycle.

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.

Lead relationships with major research universities, advising institutional leaders, research computing teams, and principal investigators on NVIDIA technologies. Drive business growth, revenue forecasting, go-to-market strategy, platform adoption, and ecosystem enablement. Build partnerships across scientific disciplines, coordinate internal technical and product teams, communicate technology roadmaps, and develop expertise in emerging computational methods. Travel approximately 25% or more and support institutions in the Northeast or Mid-Atlantic regions.

Develop and support NVIDIA networking technologies for AI clusters, including InfiniBand, NVLink, and Spectrum-X. Reproduce and root-cause complex customer issues down to source code, collaborate with R&D on fixes, analyze high-performance network metrics, and create diagnostic tools. The role requires extensive C and Python development in Linux and embedded systems, networking expertise, customer support experience, and strong communication skills. Occasional weekend or holiday support may be required.

Leads NVIDIA’s US Medtech Account Managers and drives enterprise sales growth across named manufacturing accounts. Responsibilities include demand generation, forecasting, executive relationship development, channel and partner collaboration, revenue target attainment, and coordination with internal teams to address customer needs. The role focuses on selling NVIDIA hardware and software for AI and accelerated computing in healthcare and medtech markets.