Research Software Engineer

National Institute of Standards and Technology; Gaithersburg (MD); On-site; USD 70,000 - 90,000; Full time

Job summary

The Data Science and Artificial Intelligence Group (DSAI) at NIST is seeking a Research Software Engineer to lead and contribute to sustainable software infrastructure for AI-enabled materials and chemical science. You will embed with multiple projects, focusing on databases, AI pipelines, and reproducible research software used by NIST researchers and the broader community.

You will shape software practices, participate in planning and code reviews, and help translate research prototypes into

Qualifications

• Bachelor’s or Master’s degree in a STEM field or equivalent experience.
• Experience with API design, release management, and documentation for scientific users.
• Experience enabling automated testing and CI in software projects.
• Ability to perform code reviews and promote maintainability of software.
• Experience with data pipelines, reproducible workflows, and scientific computing in Python.

Responsibilities

• Provide technical leadership and hands-on development for high-impact projects.
• Design and deploy scientific databases to support research and public datasets.
• Build infrastructure for AI-enabled science projects and autonomous platforms.
• Refactor, profile, test, and package prototype research code for long-term use.
• Support ML workflows, benchmark suites, and reproducible evaluation pipelines.

Skills

API design

Release management

Documentation

Automated testing

CI / Continuous integration

Code review

Maintainability practices

Education

Bachelor’s degree in STEM fields

Master’s degree (preferred)

Tools

FastAPI

Django

PyTorch

Job description

The Data Science and Artificial Intelligence Group (DSAI) in the NIST Material Measurement Laboratory is seeking a Research Software Engineer (RSE) to help build sustainable software infrastructure for AI-enabled materials and chemical science (U.S. citizens preferred). The successful candidate will provide both leadership and hands-on engineering support for the development, maintenance, deployment, and long-term sustainability of critical research software, databases, workflows, and public scientific infrastructure.

In this role, you will work as an embedded technical team member across multiple DSAI projects, participating in project planning, code review, architecture discussions, reproducibility efforts, and deployment decisions. You will have the opportunity to shape software practices in a growing AI for science group, contribute to public scientific datasets and benchmarks, and help translate research prototypes into reliable software tools, simulation and benchmarking workflows, and measurement capabilities used by NIST researchers and the broader community to accelerate development and deployment of new materials technologies. The successful candidate will help prioritize engineering work across projects in consultation with DSAI scientists, balancing near-term research needs with long-term software sustainability.

Duties

You will provide technical leadership and hands-on development for several high-impact projects. Key responsibilities include:

• Design and deploy scientific databases supporting active research and public datasets.
• Build and maintain infrastructure for self-driving laboratory projects, including ongoing work on an autonomous metal-organic framework synthesis platform and high-speed synchrotron characterization project.
• Refactor, profile, test, and package prototype research code for long-term maintainability and performance.
• Support scientific machine learning workflows, benchmark suites, and reproducible ML evaluation pipelines.
• Develop a user-friendly, intuitive websites for unique scientific datasets, for example DSAI’s newly curated quantum transport database of semiconductor interfaces.

Professional Development Opportunities

NIST is a collaborative research environment that provides access to scientists and metrologists with deep expertise in a broad range of application areas. Potential career development opportunities of this RSE position include:

• Opportunity to build a portfolio of reusable tools, databases, and research platforms for advanced simulation and measurement science capabilities in AI for science.
• Collaboration with domain scientists on cutting-edge AI for science problems.
• Broad exposure to current needs, community, and research directions in AI accelerated science.

Required Skills, Expertise, and Qualifications

• Bachelor’s or Master’s degree in a STEM field, computer science, software engineering, or equivalent professional experience.
• Software Engineering Practice: Library and API design and release management, documentation for scientific users and developers, automated testing and continuous integration, code review and maintainability practices.
• Collaborative Leadership: The ability to work alongside researchers in adopting modern, collaborative software development workflows (e.g., git-based collaboration, issue tracking, lightweight project management).
• Data Engineering: Experience building data pipelines and reproducible workflows, for example designing SQL-backed data storage and provenance systems to support computational research.
• Scientific Computing: Demonstrated software engineering experience handling numerical and scientific data, with deep familiarity with the Python numerical computing ecosystem.
• Documentation: Experience creating tutorials, examples, API documentation, or other user-facing materials for scientific software.

Preferred Qualifications (Strong Plus)

• Machine Learning Operations: Experience evaluating and deploying ML systems in reproducible research or production environments, with specific proficiency in PyTorch.
• Open source software: the ideal candidate will have a track record of contributions to open source projects and community engagement.
• Computational materials science: Familiarity with databases and workflows.
• Performance Engineering: A track record of optimizing code for speed and efficiency, with experience using profiling and debugging tools.
• GPU Computing: Familiarity with GPU-based packages, particularly those relating to machine learning interatomic potentials.
• Web Development: Experience building and deploying robust web applications using frameworks such as FastAPI, Django, or similar.

Employment Terms

This is a one year non-federal position with potential for extension. In-person role at the Gaithersburg, MD, campus.

An Associate at NIST is not a federal employee but collaborates with NIST on research projects of mutual interest and does not work exclusively on NIST mission-related activities. If you have any questions, please contact the International and Academic Affairs Office at [e-mail] .

Between $70k to $90k depending on qualifications and experience