Work with applied researchers to design, implement and test next generation of RL and pos-training algorithms
Contribute and advance open source by developing NeMo-RL , Megatron Core, 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 of computer-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
Requirements
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.
Benefits
equity
benefits
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