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.
Your work may include:
- 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.
This position qualifies as “Hybrid Remote Work - Mostly Onsite”: which applies to employees regularly scheduled for some onsite and some remote days, with employees typically working up to 40% of their time remotely.
Position Requirements
Required Qualifications:
- RD2: 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
- 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
Job Family
Research Development (RD)Job Profile
Computer Science 2Worker Type
RegularTime Type
Full timeThe expected hiring range for this position is $94,486.00 - $147,398.94.Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
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As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.
Skills Required
- RD2: Bachelor's +5 years, Master's +3 years, or PhD +0 years (or equivalent)
- Educational background in computer science, machine learning, AI, computational science, applied mathematics, or 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 AI frameworks such as PyTorch or JAX
- Experience designing, implementing, and evaluating complex AI systems
- Good verbal and written communication skills
- Ability to model Argonne core values (impact, safety, respect, integrity, teamwork)
- 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
What We Do
Argonne National Laboratory, one of the U.S. Department of Energy's national laboratories for science and engineering research, employs 3,400 employees, including 1,400 scientists and engineers, three-quarters of whom hold doctoral degrees.
