Senior Research Engineer - Enterprise Products

at Nvidia

📍 United States

USD 192,000-356,500 per year

SENIOR

✅ Remote

Used Tools & Technologies

NLP GenAI

Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Algorithms @ 4 Data Structures @ 7 Distributed Systems @ 4 Machine Learning @ 4 TensorFlow @ 7 Communication @ 7 Mentoring @ 4 LLM @ 4 PyTorch @ 7 CUDA @ 4 GPU @ 4 Deep Learning @ 7 Generative AI @ 4 AI @ 4

Details

We are looking for a Senior Research Engineer passionate about Generative AI inference. The team develops optimized inferencing technologies for generative AI models (language, images) and contributes across the ML lifecycle: conceptualization, applied research, engineering for optimized inference, and deployment. The role involves collaboration with research teams, engineers, and the open-source community.

Responsibilities

Design and evaluate routing policies for LLM traffic to best use a mixture of model systems.
Build and run agentic benchmarks (e.g., Terminal-Bench) to measure algorithm quality, and convert results into calibration data and routing profiles.
Ship to an open-source repository: design docs, code review, documentation, and community contributions.
Collaborate with engineering teams across NVIDIA to ensure seamless integration with the NVIDIA accelerated serving stack.

Requirements

Bachelor's or 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: form hypotheses about new algorithms, run calibrations, and iterate on results.
Strong communication and interpersonal skills; ability to work in a dynamic and distributed team. A history of mentoring junior engineers and interns is a plus.
Desire to constantly grow and learn new things.
Strong computer science fundamentals: algorithms and data structures, computational complexity, parallel and distributed computing, system software.

Preferred / Ways to Stand Out

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).

Technologies & Tools Mentioned

PyTorch, TensorFlow
LLMs, agentic benchmarks (Terminal-Bench)
CUDA, GPU/CPU architecture
Distributed systems and accelerated serving stacks
Open-source repositories, code review, design docs

Compensation & Additional Info

Base salary ranges provided by level:
- Level 4: 192,000 USD - 304,750 USD
- Level 5: 224,000 USD - 356,500 USD
Eligible for equity and benefits (link to NVIDIA benefits referenced).
Applications accepted at least until July 14, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is an equal opportunity employer and emphasizes an inclusive work environment.