Scientific Data Services Engineer - AI & HPC

Required skills and qualifications

• RD2: Bachelors and 5+ years of experience, Masters and 3+ years, or PhD and 0+ years, or equivalent
• Degree 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 one data management framework (e.g. OpenMetadata)
• Experience with deployment in diverse environments (e.g. Kubernetes, HPC)
• Ability to create, maintain, and support high-quality software is essential
• Experience with version control software such as git
• Ability to work collaboratively in a fast-paced environment
• Effective written and oral communications skills
• Ability to model Argonne’s core values of impact, safety, respect, integrity and teamwork

Preferred skills and qualifications

• A recent MS or PhD in computer science, computational science, a physical science, engineering, or related field
• Experience working with scientific data in one or more domains
• Experience working with parallel filesystems
• Experience designing or operating data services, including deployment, analysis, and integration with AI language models
• Experience profiling and optimizing data services for performance
• Familiarity with secure, multi-user services, including authentication/authorization, and API security

The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community. We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and computational science expertise.

The ALCF has an opening for a data services engineer working in the space of enabling AI for science, specifically targeting large-scale scientific data management. The successful candidate will join the Data Services and Workflows group, which focuses on scientific workflows that combine large-scale data, simulations, analysis, and AI. In this position, the candidate can expect to engineer solutions that expose terabytes to petabytes of scientific data to users and to AI models, emphasizing data ingestion, indexing, and search of diverse data. Working together with scientists, you will work to understand data from target science domains, how to structure it efficiently for search according to project requirements, and expose it to users through highly-usable web applications, and to AI applications through high-performance APIs.

The Data Services and Workflows group–and this position–involves work in a highly collaborative environment involving science application teams, academia and industry, as well as other national labs and agencies, to solve some of the world’s largest and most complex problems in science and engineering. The candidate will engage with science application teams and contribute to broader scientific initiatives.

This position qualifies as “Hybrid Remote Work - Occasionally Onsite”: which applies to employees typically working more than 60% of their time remotely.