Argonne National Laboratory · 3 months ago
Postdoctoral Appointee — Data Infrastructure and Software for AI
Lemont, IL USA
Full-time
Onsite
New Grad, Entry Level
$71K/yr - $118K/yr
0+ years expArgonne National Laboratory is a leader in scientific computing, and they are seeking a postdoctoral appointee to work on data management targeting AI applications at scale. The role involves developing and scaling data infrastructure and software for AI applications on supercomputing systems, focusing on multimodal data management to accelerate scientific discovery.
EnergySecuritySocial Impact
Responsibilities
The goal for this postdoctoral position to work on development and scaling of the data infrastructure and software for AI applications on supercomputing systems and AI testbed systems
The postdoc will work on multimodal data management for science applications, focusing on integrating, organizing, and analyzing diverse data types to accelerate scientific discovery and innovation
Another goal is to develop and evaluate vector databases and retrieval-augmented generation (RAG) and integrate agentic AI systems to meet the demands of large-scale fine-tuning and inference
The postdoc will also work on design and implement agentic-AI workflows using the Model Context Protocol (MCP) to orchestrate data ingest and data movement across heterogeneous storage systems, including object stores
The postdoc will also engage with science application teams and contribute to broader initiatives, including the American Science Cloud (AmSC) AI Services efforts, and to help us with design of future systems and data-management solutions to meet needs of our applications
This postdoc position will help ALCF evaluate and integrate data infrastructure needed to better facilitate AI models, including training, fine-tuning and inferencing, at scale
It will help us better understand and improve DAOS to meet the needs of AI-driven science applications
We expect the postdoc to help prototype, benchmark, and evaluate strategies to better support these workloads for Aurora
Qualification
Required
A recent PhD (completed within the last 0-5 years) in computer science, computational science, a physical science, engineering, or related field
Comprehensive experience programming in one or more programming languages such as Python, C/C++
Experience with at least of one of the AI frameworks is required, such as PyTorch, TensorFlow
Ability to create, maintain, and support high-quality software is essential
Work with and contribute to domain-specific software and models
Experience with version control software such as git is essential
Effective written and oral communications skills
Ability to model Argonne's core values of impact, safety, respect, integrity and teamwork
Preferred
Experience with running simulations or AI workflows on supercomputers
Experience with training or applying large language models for research
Experience with MPI and Input/Output (I/O), and data management
Experience in writing technical papers and presentations
Benefits
Comprehensive benefits are part of the total rewards package
Company
Argonne National Laboratory
Argonne National Laboratory conducts researches in basic science, energy resources, and environmental management.
1001-5000 employees
H1B Sponsorship
Argonne National Laboratory has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2022 (6)
2021 (2)
Funding
Current Stage
Late StageTotal Funding
$41.4MKey Investors
Advanced Research Projects Agency for HealthUS Department of EnergyU.S. Department of Homeland Security
2024-11-14Grant· $21.7M
2023-09-27Grant
2023-01-17Grant
Leadership Team
Paul Kearns
Laboratory Director
Venkat Srinivasan
Director, Argonne Center for Collaborative Energy Storage Science (ACCESS)
Recent News
Inside HPC & AI News | High-Performance Computing & Artificial Intelligence
2026-01-17
2026-01-16
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