Top Tech Jobs & Startup Jobs in NYC, NY

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.

Leads technical developer-relations strategy for NVIDIA platforms across capital markets. Advises quants, traders, developers, financial institutions, ISVs, and cloud providers; demonstrates CUDA, CUDA-X, AI frameworks, and accelerated computing solutions; supports partner onboarding and integrations; develops benchmarks, sample code, and reference implementations; gathers ecosystem feedback; influences product roadmaps; and represents NVIDIA at industry events, workshops, and conferences.

Lead founding AI Safety & Security Engineering team, define harness architecture and engineering standards, drive Find/Validate/Patch roadmap, mentor engineers, and translate research into production-grade, secure ML systems.

Develop and formalize methods to validate reported vulnerabilities and generate/verify safe patches for internal NVIDIA targets. Define correctness, regression, and revalidation standards; produce repeatable, auditable processes and evidence. Apply AI-assisted workflows cautiously, perform bounded applied research on vulnerability classes, and document findings for independent security review.

Supports and root-causes complex customer issues involving NVIDIA networking and AI cluster technologies. Develops bug fixes, workarounds, diagnostic tools, and performance-tuning recommendations in collaboration with R&D and support teams. Works with InfiniBand, NVLink, Spectrum-X, and high-performance lossless networks, analyzing logs, traces, metrics, and source code. Provides customer support and may work occasional weekends or holidays.

Build and maintain network automation and orchestration software for NVIDIA GPU Cloud and SuperPod deployments. Design/configure centralized configuration management, integrate cloud provider APIs, implement data pipelines and streaming telemetry, and automate lifecycle operations from procurement to deployment. Collaborate with infrastructure experts to deliver zero-touch, production-grade network provisioning, monitoring, and management tools.

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.

Partners with customers and internal teams to design, deploy, and optimize generative AI and LLM inference solutions. Develops proofs of concept, supports NVIDIA technology adoption, analyzes AI workload performance and power efficiency on Kubernetes, and advises developers, researchers, and data scientists. The role requires expertise in deep learning frameworks, GPU orchestration, MLOps, containerization, observability, and LLM inference, with occasional travel to conferences and customers.

Develop and deploy deep learning models and petabyte-scale multimodal data curation pipelines for foundation-model training. Responsibilities include document extraction, OCR, layout and table analysis, deduplication, distributed processing, dataset and metric development, experimentation, production scaling, and deployment through NVIDIA Inference Microservices. The role also involves publishing research, creating technical documentation, communicating findings, and mentoring team members.

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.