Principal Machine Learning Engineer - Supply Chain

at Nvidia
📍 Santa Clara, United States
USD 272,000-425,500 per year
SENIOR
✅ Hybrid

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Python @ 7 R @ 4 Machine Learning @ 4 TensorFlow @ 7 NLP @ 4 LLM @ 4 PyTorch @ 7 CUDA @ 3

Details

NVIDIA Enterprise AI is seeking a Principal Machine Learning Engineer to lead the creation and productionization of advanced AI solutions focused on optimizing complex, global supply chains that support NVIDIA's chip design and manufacturing programs. The role spans NLP and Generative AI solutions, combinatorial optimization, and building ML-powered applications and optimization engines to improve supply-chain efficiency and resilience.

Responsibilities

  • Develop intelligent AI solutions leveraging NVIDIA AI technologies and GPUs to build NLP and Generative AI systems (e.g., RAG pipelines, agentic workflows) that address enterprise and supply-chain problems.
  • Lead AI product development: guide engineers and researchers to build LLM-powered applications, chatbots, and optimization engines that improve chip-design supply-chain outcomes.
  • Design ML and optimization architectures including machine learning and combinatorial-optimization approaches (examples: multi-echelon inventory, yield-constrained scheduling, supplier risk mitigation), with familiarity or use of NVIDIA cuOpt where applicable.
  • Collaborate closely with supply-chain operations teams to identify high-impact opportunities, translate requirements into ML solutions, and drive measurable business results.
  • Drive end-to-end ML systems design and production deployment, including data ingestion, model serving, monitoring, and continuous improvement.

Requirements

  • Demonstrated, hands-on experience applying AI techniques to supply-chain challenges (examples: demand forecasting, wafer-level yield optimization, capacity planning, material logistics, supplier risk analytics).
  • 12+ years of experience designing, building, and deploying ML models and systems in production.
  • Master’s or Ph.D. in Computer Science, Operations Research, Industrial Engineering, or a related technical field, or equivalent experience.
  • Expert-level Python and strong experience with deep learning frameworks such as PyTorch or TensorFlow.
  • Strong knowledge of transformers, attention mechanisms, and modern NLP/GenAI techniques. Experience with Retrieval-Augmented Generation (RAG) and agentic workflows is expected.
  • Familiarity with CUDA-accelerated libraries and NVIDIA inference/optimization tooling (examples cited: cuOpt, TensorRT-LLM) is a plus.
  • Proven ability to think independently, drive R&D efforts, and mentor multidisciplinary engineering teams.

Ways to Stand Out

  • Practical experience with agentic-AI frameworks (e.g., LangChain or LangGraph) and multi-step reasoning/planning.
  • Expertise in LLM inference optimization (e.g., KV caching) to achieve sub-second latency at scale.
  • Portfolio showing ownership of the full ML lifecycle from data ingestion to monitoring and continuous improvement.
  • Research impact such as publications or patents in NLP or supply-chain AI.

Benefits & Additional Info

  • Base salary range: 272,000 USD - 425,500 USD (determined by location, experience, and comparable pay). You will also be eligible for equity and NVIDIA benefits.
  • Applications accepted at least until July 29, 2025.
  • NVIDIA is an equal opportunity employer committed to diversity and inclusion.