Nvidia Senior Research Engineer 

United States, Texas 

842940841

What you’ll be doing:

• Work with applied researchers to design, implement and test next generation of RL and pos-training algorithms

• Contribute and advance open source by developing , and NeMo Framework and yet to be announced software

• You will be engaged as part of one team during Nemotron models post-training

• Solve large-scale, end-to-end AI training and inference challenges, spanning the full model lifecycle from initial orchestration, data pre-processing, running of model training and tuning, to model deployment.

• Work at the intersection ofcomputer-architecture,libraries, frameworks, AI applications and the entire software stack.

• Performance tuning and optimizations, model training with mixed precision recipes on next-gen NVIDIA GPU architectures.

• Publish and present your results at academic and industry conferences

What we need to see:

• BS, MS or PhD in Computer Science, AI, Applied Math, or related fields or equivalent experience

• 3+ years of proven experience in machine learning, systems, distributed computing, or large-scale model training.

• Experience with AI Frameworks such as Pytorch or JAX

• Experience with at least one inference and deployment environments such as vLLM, SGLang or TRT-LLM

• Proficient in Python programming, software design, debugging, performance analysis, test design and documentation.

• Strong understanding of AI/Deep-Learning fundamentals and their practical applications.

Ways to stand out from the crowd:

• Contributions to open source deep learning libraries

• Hands-on experience in large-scale AI training, with a deep understanding of core compute system concepts (such as latency/throughput bottlenecks, pipelining, and multiprocessing) and demonstrated excellence in related performance analysis and tuning.

• Expertise in distributed computing, model parallelism, and mixed precision training

• Prior experience with Generative AI techniques applied to LLM and Multi-Modal learning (Text, Image, and Video).

• Knowledge of GPU/CPU architecture and related numerical software.