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Scientific Data Services Engineer – AI & HPC

Argonne National Laboratory · Lemont, IL · $94,486–$147,399 a year · Full time

Posted Apr 23, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

When you start with a new science team, how do you learn enough about their data to decide how it should be structured for search?

What they are checking: Whether they listen to domain scientists and let the science drive the data model instead of forcing a generic schema.

Tell me about a time a data pipeline you built broke in production. How did you find the cause?

What they are checking: Whether they debug systematically and build in monitoring, since silent data errors can ruin research results.

Tell me about a project where you worked closely with scientists. What did you learn from how they think about data?

What they are checking: Whether they thrive in the highly collaborative, cross-discipline environment this group depends on.

What would you do

A model team wants to train on a dataset that lives across several file systems in formats like HDF5 and NetCDF. How would you make it easy for them to stream it?

What they are checking: Whether they know how scientific file formats and parallel file systems behave when feeding AI workloads.

Two science projects want different features from your data service and you only have time for one. How do you decide?

What they are checking: Whether they can weigh scientific impact and number of users and explain a fair decision to both groups.

About the work

How would you design a system to ingest and index a few petabytes of mixed scientific data so researchers can search it quickly?

What they are checking: Whether they can think about ingestion, metadata, and indexing at real scale rather than at laptop scale.

What search technologies have you used, such as Elasticsearch, OpenSearch or vector databases, and how did you choose between them?

What they are checking: Whether they understand the tradeoffs between keyword, faceted and vector search for different kinds of scientific queries.

How would you expose the same dataset both to people through a web app and to AI models through a high-performance API?

What they are checking: Whether they can serve two very different consumers without duplicating data or creating two systems that drift apart.

How do you think about provenance and versioning for scientific data that keeps changing as new runs come in?

What they are checking: Whether they understand that reproducibility in science depends on knowing exactly which data a result came from.

What makes a scientific data web application actually usable for a researcher who is not a software person?

What they are checking: Whether they care about the end user experience and not just the backend architecture.

How have you used HPC resources, schedulers or workflow tools in past data projects?

What they are checking: Whether they can work inside a supercomputing environment where jobs, storage and networks behave differently from the cloud.

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The full job description

As published by Argonne National Laboratory.

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. Position Requirements 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 Job Family Research Development (RD) Job Profile Software Engineering 2 Worker Type Regular Time Type Full time The 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. Click here to view Argonne employee benefits! 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.

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