Build hands-on PoCs, benchmarks, reference architectures, and reusable blueprints that help Enterprise ISVs and NVIDIA field teams move from exploration to production.
Guide partners on model customization and post-training workflows, including supervised fine-tuning, reinforcement learning methods, human or AI feedback, direct preference optimization, PEFT/LoRA, synthetic data generation, evaluation, and regression analysis.
Work with agent harnesses and execution environments such as OpenShell, OpenAI Agents SDK, LangGraph, LlamaIndex, LangChain, CrewAI, Semantic Kernel, or similar frameworks.
Translate partner deployment findings into actionable feedback for NVIDIA Product and Engineering, so we can improve our platforms, tools, and field guidance.
What we need to see
BS/MS/PhD in Computer Science, Electrical Engineering, AI/ML, or equivalent experience.
8+ years of engineering, solutions architecture, applied ML, or technical deployment experience.
Consistent track record leading complex AI, ML, distributed systems, or enterprise software deployments from prototype to production.
Hands-on experience building LLM, generative AI, RAG, or agentic AI applications in production or production-like environments.
Strong programming and debugging skills in Python and Linux environments, with experience in PyTorch, TensorFlow, or similar deep learning frameworks.
Deep understanding of agentic AI architectures, including tool use, orchestration, memory, retrieval, planning, evaluation, guardrails, and failure handling.
Experience with model customization or post-training techniques such as SFT, RL/RLHF/RLAIF, DPO or relevant equivalent experience, reward modeling, LoRA/PEFT, quantization-aware optimization, or model evaluation.
Ability to lead ambiguous partner engagements, influence senior engineering collaborators, and communicate clearly with technical and executive audiences.
Ways to stand out from the crowd
Hands-on experience with NVIDIA AI software such as NIM, NeMo Framework, NeMo Retriever, NeMo Guardrails, NeMo Agent Toolkit, Dynamo, Nemotron, Triton, TensorRT-LLM, or NIM Operator.
Experience building post-training pipelines for reasoning, tool use, domain adaptation, enterprise task performance, or agent behavior improvement.
Experience with agent harnesses, sandboxed execution, policy enforcement, OpenShell-like environments, or secure enterprise agent runtime build.
Recognized expertise in RAG, model customization, agent orchestration, enterprise AI security, or GPU-accelerated AI infrastructure, with field-facing technical presence through workshops, architecture reviews, talks, whitepapers, or developer enablement.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 184,000 USD – 287,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
