Staff Scientist: Post-Training & RL for AI in Science

Argonne National Laboratory; United States; Híbrido; USD 94 000 - 147 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Comprehensive benefits

Resumo da oferta

Argonne National Laboratory seeks a Staff Scientist in Post-Training and Reinforcement Learning for AI for Science to advance foundation models and learning systems for scientific discovery at leadership-class supercomputers.

You will develop, scale, and evaluate post-training methods including reinforcement learning and alignment techniques for scientific AI models and workflows, collaborating across AI, simulation, and domain science while contributing to high-impact publications and

Qualificações

• Bachelor's degree or higher in CS or related field.
• Advanced knowledge in machine learning, reinforcement learning, large-scale model training, post-training, optimization, data mining, or statistics.
• Strong background in mathematical optimization, linear algebra, or numerical methods.
• Programming experience in Python, C, or C++.
• Experience with ML frameworks such as PyTorch or JAX.
• Experience with large-scale training and post-training workflows.
• Ability to work in interdisciplinary teams.

Responsabilidades

• Conduct research and development aligned with Argonne's mission in computation, AI, and scientific discovery.
• Develop, scale, and optimize post-training methods for scientific foundation models, including RL, preference-based optimization, fine-tuning, alignment.
• Advance techniques to improve performance, controllability, and reliability of AI models for science.
• Design and evaluate methods for applying RL and post-training pipelines to large-scale environments.
• Develop and optimize workflows for training on leadership-class supercomputers and AI-oriented architectures.
• Collaborate with computational scientists and domain researchers on challenging problems.
• Address algorithmic, systems, and data challenges with large-scale training and post-training.

Conhecimentos

Python

C/C++

Machine Learning / Reinforcement

Optimization

Distributed training

Communication skills

Interdisciplinary collaboration

Formação académica

Bachelor's degree

Master's degree

PhD

Related field degree

Ferramentas

PyTorch

JAX

TensorFlow

Linux

Descrição da oferta de emprego

Argonne National Laboratory seeks a Staff Scientist in Post-Training and Reinforcement Learning for AI for Science to advance foundation models and learning systems for scientific discovery at leadership-class supercomputers.

You will develop, scale, and evaluate post-training methods including reinforcement learning and alignment techniques for scientific AI models and workflows, collaborating across AI, simulation, and domain science while contributing to high-impact publications and