NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC-gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU-accelerated deep learning ignited modern AI—the next era of computing—with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.”We are seeking a Senior Staff Machine Learning Engineer to join our Enterprise AI team and build intelligent, scalable solutions that transform enterprise operations. You will develop and productionize advanced AI systems spanning smart assistants, software-engineering productivity, and data-driven analytics.What You’ll Be Doing:Develop Intelligent AI Solutions – Leverage NVIDIA AI technologies and GPUs to build pioneering NLP and Generative AI solutions—such as Retrieval-Augmented Generation (RAG) pipelines and agentic workflows—that solve real-world enterprise and supply-chain problems.Own Key AI Features – Drive the end-to-end development of LLM-powered applications, chatbots, and optimization engines that improve organizational efficiency and resilience.Design Robust ML Architectures – Create machine-learning and combinatorial-optimization designs targeting high-impact challenges across employee productivity, engineering efficiency, AIOps, and supply-chain operations, etc..Collaborate Across NVIDIA – Work closely with product, research, and engineering teams to translate requirements into ML solutions and deliver measurable business outcomes.Mentor & Share Best Practices – Guide junior engineers and peers on ML design patterns, code quality, and experiment methodology.What We Need to See:Master’s or Ph.D. in Computer Science, Operations Research, Industrial Engineering, or a related field, or equivalent experience.10+ years designing, building, and deploying machine-learning models and systems in production with 12+ years industry experience.Solid understanding of transformers, attention mechanisms, and modern NLP / LLM techniques; experience fine-tuning or prompting large language models.Strong Python plus deep-learning frameworks such as PyTorch or TensorFlow; familiarity with CUDA-accelerated libraries (e.g., TensorRT-LLM) is a plus.Proven track record to take a significant ML component or feature from concept to production and collaborate effectively with multi-functional teams.Ways to Stand Out from the Crowd:Agentic AI Mastery – Practical experience with frameworks such as LangChain or LangGraph and a deep understanding of multi-step reasoning and planning.LLM Inference Optimization – Expertise in accelerating LLM inference (e.g., KV caching, quantization) to achieve low latency at scale.End-to-End ML Systems Ownership – A portfolio showing full lifecycle ownership, from data ingestion to monitoring and continuous improvement.Research Impact – Publications or patents that advance NLP or enterprise AI.NVIDIA is widely considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people on the planet working for us. If you’re creative, autonomous, and excited about shaping the future of Enterprise AI, we want to hear from you!#LI-HybridYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 425,500 USD for Level 6.You will also be eligible for equity and benefits.Applications for this job will be accepted at least until August 16, 2025.NVIDIA is committed to fostering a diverse 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.