Used Tools & Technologies
GenAIRequired 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.
Python @ 6
Algorithms @ 4
Data Structures @ 4
Distributed Systems @ 4
Machine Learning @ 4
LLM @ 4
PyTorch @ 6
Deep Learning @ 4
Generative AI @ 4
AI @ 4
Data Pipelines @ 4
- 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.
Details
We are looking for a Senior Research Scientist passionate about Large Language Model (LLM) and Diffusion Language Model (DLM) post-training and system optimization. NVIDIA works on foundation models and generative AI systems, advancing post-training algorithms, building efficient large-scale systems, and developing evaluation frameworks for reliability and scalability.
Responsibilities
- Design and implement post-training algorithms for LLMs and DLMs.
- Drive efficiency and scalability improvements across training pipelines and serving systems.
- Collaborate with researchers to translate cutting-edge ideas into production-ready implementations.
- Explore new paradigms for evaluation.
- Demonstrate strong engineering practices and contribute to open-source communities.
Requirements
- PhD in Computer Science, Electrical Engineering, or related field, or equivalent research experience in LLMs, systems, or related areas.
- 2+ years of experience in machine learning, systems, distributed computing, or large-scale model training.
- Proficiency in Python with hands-on experience in frameworks such as PyTorch.
- Solid background in computer science fundamentals: algorithms, data structures, parallel/distributed computing, and systems programming.
- Proven ability to collaborate across research and engineering teams in multifaceted environments.
Ways to Stand Out
- Expertise in post-training LLMs with novel algorithmic/data pipelines.
- Experience developing and scaling large distributed systems for deep learning.
- Contributions to open-source LLM systems or large-scale AI infrastructure.
Compensation & Benefits
- Base salary range (Level 3): 168,000 USD - 264,500 USD.
- Base salary range (Level 4): 192,000 USD - 304,750 USD.
- You will also be eligible for equity and benefits.
Additional Information
- Applications for this job will be accepted at least until March 27, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.