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# Senior Research Engineer - Enterprise Products

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, UT, United States
- **Experience:** Expert
- **Salary:** $192,000.0 - $304,750.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Artificial Neural Networks, Code Review, Nvidia CUDA, Distributed Systems, Machine Learning, Language Modeling, Natural Language Processing, Open Source Technology, Tensorflow, System Software, Speech Recognition, Graphics Processing Unit (GPU), Pytorch, Large Language Models, Deep Learning, Gpu Programming, Agentic-AI, Information Technology
- **Published:** October 29, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-research-engineer-enterprise-products-santa-clara-ut--b4f19d18-5db3-44a9-9321-f0d62a85964f

## About the Role

Machine Learning, Artificial Intelligence (AI), Technical Support, Modeling Languages, Policy Evaluation, Open Source, Code Reviews, Computer Science, Benchmarking, Speech Recognition, * Bachelor's of Master's degree in Computer Science or equivalent experience.

 * 8+ years of industry experience in Deep Learning frameworks (PyTorch or TensorFlow).
 * Experience designing or running LLM evaluations/benchmarks - ideally agentic ones - and drawing statistically sound conclusions from them
 * Understanding of modern techniques in Machine Learning, Deep Neural Networks, Natural Language Processing, or Speech Recognition.
 * Empirical research mindset: forming hypotheses about new algorithms, running calibrations, iterating on results
 * Strong communication and interpersonal skills, along with the ability to work in a dynamic and distributed team. A history of mentoring junior engineers and interns is a huge plus.
 * A desire to constantly grow and learn new things.
 * Strong computer science fundamentals - algorithms and data structures, computational complexity, parallel and distributed computing, system software.

Ways to stand out from a crowd:

 * Experience architecting or developing large-scale distributed systems for deep learning.
 * Agentic benchmark creation and publications.
 * Knowledge of CPU and/or GPU architecture.
 * GPU programming (CUDA).