Principal Machine Learning Engineer - Enterprise AI

Orange County Comptroller; Santa Clara (CA); On-site; USD 272,000 - 426,000; Full time

Job summary

NVIDIA seeks a Principal Machine Learning Engineer to transform enterprise AI solutions focusing on supply chain optimization. This role involves developing cutting-edge AI systems, collaborating with teams, and effectively applying machine learning to complex challenges. Candidates should have extensive experience and advanced degrees in relevant fields.

Benefits

Equity and benefits

Diverse work environment

Qualifications

• 12+ years of experience in designing and deploying ML models.
• Hands-on experience with AI techniques for supply chain.

Responsibilities

• Develop intelligent AI solutions for supply chain problems.
• Lead AI product development and guide engineering teams.

Skills

Python

Machine Learning

AI Techniques

Deep Learning

NLP

Education

Master's or Ph.D. in Computer Science

Tools

PyTorch

TensorFlow

Job description

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 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 PrincipalMachineLearningEngineer to join our EnterpriseAI team and lead the creation of intelligent, scalable AI solutions that transform enterprise operations-with a special focus on optimizing the complex, global supply chains that underpin NVIDIA's chip‑design and manufacturing programs. You will develop and productionize advanced AI systems spanning smart assistants, software‑engineering productivity, analytics, and, critically, semiconductor supply‑chain optimization.

What You'll Be Doing:

• Develop Intelligent AI Solutions - Leverage NVIDIA AI technologies and GPUs to build cutting‑edge NLP and GenerativeAI solutions-such as Retrieval‑Augmented Generation (RAG) pipelines and agentic workflows-that solve real‑world enterprise and supply‑chain problems.
• Lead AI Product Development - Guide engineers and researchers in developing large‑language‑model-powered applications, chatbots, and optimization engines that directly improve chip‑design supply‑chain efficiency and resilience.
• Design ML & Optimization Architectures - Create and implement machine‑learning and combinatorial‑optimization architectures (e.g., using NVIDIA cuOpt) tailored to semiconductor supply‑chain use cases such as multi‑echelon inventory, yield‑constrained scheduling, and supplier risk mitigation.
• Collaborate Across NVIDIA - Partner with supply‑chain operation teams to identify high‑impact opportunities, translate requirements into ML solutions, and drive measurable business outcomes.

What We Need to See:

• Master's or Ph.D. in Computer Science, Operations Research, Industrial Engineering, or a related technical field, or equivalent experience.
• 12+ years of experience designing, building, and deploying ML models and systems in production.
• Demonstrated, hands-on experience applying AI techniques to supply‑chain challenges (e.g., demand forecasting, wafer‑level yield optimization, capacity planning, material logistics, or supplier risk analytics).
• Strong knowledge of transformers, attention mechanisms, and modern NLP/GenAI techniques.
• Expert‑level Python plus deep‑learning frameworks such as PyTorch or TensorFlow; familiarity with CUDA‑accelerated libraries (cuOpt, TensorRT‑LLM) is a plus.
• Proven ability to think independently, drive research and development efforts, and mentor multidisciplinary engineering teams.
• Highly motivated, curious, and eager to push the boundaries of what AI can do for complex supply‑chain systems.

Ways to StandOut from the Crowd:

• AgenticAI Expertise - 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) to achieve sub‑second latency at scale.
• End‑to‑End ML Systems Design - A portfolio showing ownership of the full ML lifecycle, from data ingestion to monitoring and continuous improvement.
• Research Impact - Publications or patents that advance NLP, or supply‑chain 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-Hyrbrid

The base salary range is 272,000 USD - 425,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits . NVIDIA accepts applications on an ongoing basis.

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.