Senior Staff Machine Learning Engineer — Enterprise AI

Details

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.

Responsibilities

• Develop intelligent AI solutions using NVIDIA AI technologies and GPUs to build NLP and generative AI solutions such as Retrieval-Augmented Generation (RAG) pipelines and agentic workflows that address enterprise and supply-chain problems.
• Own key AI features: drive end-to-end development of LLM-powered applications, chatbots, and optimization engines to improve organizational efficiency and resilience.
• Design robust ML architectures: create machine-learning and combinatorial-optimization solutions targeting challenges across employee productivity, engineering efficiency, AIOps, and supply-chain operations.
• Collaborate across product, research, and engineering teams to translate requirements into ML solutions and deliver measurable business outcomes.
• Mentor and share best practices: guide junior engineers and peers on ML design patterns, code quality, and experiment methodology.

Requirements

• 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 of industry experience.
• Solid understanding of transformers, attention mechanisms, and modern NLP / LLM techniques; experience fine-tuning or prompting large language models.
• Strong Python skills and experience with deep-learning frameworks such as PyTorch or TensorFlow.
• Familiarity with CUDA-accelerated libraries (e.g., TensorRT-LLM) is a plus.
• Proven track record of taking significant ML components or features from concept to production and collaborating effectively with cross-functional teams.

Ways to Stand Out

• Agentic AI mastery: practical experience with frameworks such as LangChain or LangGraph and deep understanding of multi-step reasoning and planning.
• LLM inference optimization expertise (e.g., KV caching, quantization) to achieve low latency at scale.
• End-to-end ML systems ownership: portfolio showing full lifecycle ownership from data ingestion to monitoring and continuous improvement.
• Research impact: publications or patents that advance NLP or enterprise AI.

Compensation & Benefits

• Base salary ranges by level:
  • Level 5: 224,000 USD - 356,500 USD
  • Level 6: 272,000 USD - 425,500 USD
• You will also be eligible for equity and benefits.

Additional Information

• This role is listed as #LI-Hybrid.
• Applications for this job will be accepted at least until July 29, 2025.
• NVIDIA is an equal opportunity employer and values diversity in hiring and promotion practices.