Staff Scientist – Agents for Science

Argonne National Laboratory•Lemont, IL

1d•Hybrid

About The Position

The Argonne Leadership Computing Facility (ALCF) is seeking a Staff Scientist – Agents for Science to help pioneer AI systems that can reason, plan, act, and collaborate in support of scientific discovery. AI for science is entering a new phase. Beyond models that analyze data or make predictions, there is growing opportunity to develop agentic AI systems that can interact with scientific data, simulations, instruments, workflows, and knowledge sources in more adaptive and autonomous ways. At ALCF, we are exploring how such systems can help scientists formulate hypotheses, design experiments, navigate complex data, coordinate computational workflows, and accelerate discovery across disciplines. This role is an opportunity to work at the frontier of agentic AI, foundation models, scientific workflows, and high-performance computing, and contribute to the Department of Energy’s Genesis mission. We are looking for a creative and collaborative staff scientist/engineer who wants to develop novel methods and systems for AI agents in scientific environments and deploy them at the scale required by real scientific challenges. You will join the AI group—a highly collaborative, multidisciplinary environment and work alongside experts in AI, simulation, computer science, applied mathematics, and domain science.

Requirements

Bachelor’s degree and 5+ years of experience, or Master’s degree and 3+ years of experience, or PhD and 0+ years of experience, or equivalent Educational background in computer science, machine learning, artificial intelligence, computational science, applied mathematics, or a related field, PhD preferred
Experience with reinforcement learning, planning, or sequential decision-making
Strong programming skills in one or more languages such as Python, C, C++
Experience with one or more AI frameworks such as PyTorch, JAX, or related tools
Experience designing, implementing, and evaluating complex AI systems
Good communication skills, both verbal and written.
Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork

Nice To Haves

Experience with LLM-based systems, retrieval-augmented generation, tool calling, or workflow agents
Experience integrating AI systems with scientific software, simulations, databases, or experimental workflows
Experience with distributed training, inference systems, or HPC environments

Responsibilities

Designing and developing agentic AI systems for scientific discovery, including systems that can reason, plan, retrieve information, invoke tools, and execute multi-step scientific tasks
Developing agents that can interact with simulation workflows, data pipelines, scientific software, instruments, knowledge bases, and computational tools
Building methods for tool use, workflow orchestration, memory, planning, adaptation, and decision-making in scientific environments
Evaluating agent performance in terms of scientific usefulness, reliability, robustness, efficiency, and safety
Conduct research and development aligned with Argonne’s strategic mission in computation, AI, and scientific discovery.
Contribute to a team culture that values scientific excellence, collaboration, innovation, and inclusive professional growth.