Top Tech Jobs & Startup Jobs

Design, develop, and evaluate agentic AI systems for scientific discovery, integrating agents with simulations, data pipelines, instruments, workflows, and knowledge bases. Build methods for planning, memory, tool use, workflow orchestration, and decision-making. Deploy and scale systems in HPC/distributed environments, assess scientific usefulness, reliability, robustness, efficiency, and safety, and collaborate with multidisciplinary teams to advance Argonne's AI and scientific missions.

Administer and maintain AI/ML and HPC testbed infrastructure: install and manage Linux systems, configuration management, version control, scripting, datacenter hardware operations, networking support, documentation, and collaborate with researchers and operations teams to ensure testbed availability and sustainability.

Conduct research and develop post-training and reinforcement learning methods for scientific foundation models, optimize large-scale training and post-training workflows on leadership-class supercomputers, and collaborate with multidisciplinary teams to apply adaptive learning systems to high-impact scientific problems, publishing and communicating results.

Design, build, operate, and maintain high-power solid-state RF amplifier systems (10 MHz–1 GHz). Use circuit simulation for amplifier optimization, implement interlocks, troubleshoot faults, lead R&D, and develop maintenance and operational guidelines for accelerator RF systems.

Engineer large-scale scientific data services to enable AI for science: design data ingestion, indexing, and search for terabyte-to-petabyte datasets; expose data via high-performance APIs and usable web apps; deploy and optimize services in Kubernetes and HPC environments; collaborate with scientists and partners on data structuring, performance profiling, and secure multi-user access.

Lead design, development, integration, and sustainment of laboratory and field-deployable sensing, monitoring, and control systems. Maintain and improve software tools, design hardware/firmware/PCB solutions, develop embedded Linux systems, implement secure networked communications and DSP in real-time, create GUIs and databases, and support field deployments and system modernization.

Develop and apply ML and statistical methods for experimental data, maintain and document analysis methods, collaborate with engineers to transition algorithms to prototypes, support field integration and testing, and conduct theoretical and experimental evaluation. Travel up to 15% for deployments and data collection.

Lead research developing AI/ML methods and closed-loop experimental workflows for autonomous nanoscale materials synthesis. Implement active learning, inverse design, and real-time multimodal data analysis; integrate edge, beamline, and HPC infrastructures; collaborate with synthesis and characterization teams; publish and guide future autonomous materials research.