Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,319 postings in the last year. Stated ranges, not salaries paid.
Research Software Engineer, UD Institute for Data Science
- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild and maintain open-source research software and cyberinfrastructure
Help researchers deploy and scale workflows on high-performance computing systems
Set up version control, testing, pipelines, and documentation for research code
Train and advise researchers on software engineering and shared HPC environments
Serve as computational liaison to research computing and IT groups
From the employer’s posting
build, validate, and maintain robust and scalable open-source software tools and cyberinfrastructure
Assist researchers to develop, deploy, scale, and optimize workflows that effectively and efficiently use these high-performance computing resources.
establish software version control, pipelines, institute standard testing frameworks, maintain documentation
Educate, train, and advise both novice and experienced researchers regarding software engineering, shared high performance computing environments
Serve as a computational liaison to research computing and IT groups at UD and partner institutions.
What you’ll bring
All qualificationsCore experience
- Bachelor’s degree in computer science, electrical and computer engineering, data science, statistics, biomedical engineering, mechanical engineering, operations research, robotics, computational neuroscience, applied mathematics, physics, or a closely-related discipline and five years of related work experience.
- Experience with the Linux operating system and utilizing the command line interface.
- Hands-on experience with shared high-performance computing environments and workload scheduling tools (e.g., SLURM).
- Ability to work effectively with researchers (both computational and non-computational) within multi-institutional teams to define, clarify, and execute requirements and goals.
- Ability to manage multiple projects, keeping oriented to the goals and tracking details, efficiently communicating on issues and outcomes, and executing independently and in collaboration.
Preferred experience
- Master’s or PhD is preferred.
- Experience with parallel computing, GPU operation (CUDA Toolkit), multi-GPU training, and distributed frameworks for machine learning (e.g.
- Experience with modern collaborative productivity environments (e.g., Slack, Trello, etc.).
- Experience utilizing AI-assisted programming environments (e.g., GitHub Copilot, Codex, Cursor, or LLM-driven coding tools) to streamline software development, unit testing, and refactoring.
Qualification wording
Bachelor’s degree in computer science, electrical and computer engineering, data science, statistics, biomedical engineering, mechanical engineering, operations research, robotics, computational neuroscience, applied mathematics, physics, or a closely-related discipline and five years of related work experience. Master’s or PhD is preferred.
Experience with the Linux operating system and utilizing the command line interface. ● Demonstrated ability and experience with scripting and programming languages (Bash, Python).
Hands-on experience with shared high-performance computing environments and workload scheduling tools (e.g., SLURM).
Ability to work effectively with researchers (both computational and non-computational) within multi-institutional teams to define, clarify, and execute requirements and goals.
Ability to manage multiple projects, keeping oriented to the goals and tracking details, efficiently communicating on issues and outcomes, and executing independently and in collaboration.
Experience with parallel computing, GPU operation (CUDA Toolkit), multi-GPU training, and distributed frameworks for machine learning (e.g. PyTorch Distributed).
Experience with modern collaborative productivity environments (e.g., Slack, Trello, etc.).
Experience utilizing AI-assisted programming environments (e.g., GitHub Copilot, Codex, Cursor, or LLM-driven coding tools) to streamline software development, unit testing, and refactoring.
Education & alternatives
Major Responsibilities - Participate as a member of a highly technical, research driven team, forging close working relationships with HAIC researchers (faculty, post-doctoral, students, and staff) across multidisciplinary working groups. - Provide support to HAIC researchers to use research computing hardware and software for workflows involving AI, data science, machine learning, and physics simulation, especially machine learning frameworks with interfaces for monitoring training, robust checkpointing, and validation suites.
Qualifications - Bachelor’s degree in computer science, electrical and computer engineering, data science, statistics, biomedical engineering, mechanical engineering, operations research, robotics, computational neuroscience, applied mathematics, physics, or a closely-related discipline and five years of related work experience. Master’s or PhD is preferred. - Experience with the Linux operating system and utilizing the command line interface. ● Demonstrated ability and experience with scripting and programming languages (Bash, Python).
Posting record
Report an errorActively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 29, 20268 days ago
- Recorded sightings
- 35
- Last seen by us
- Nov 6, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 8
Similar jobs usually come down between day 6 and day 71.
From 4,610 similar postings that came down. Coming down is not always a hire.
University of Delaware is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Bash
- Python
- PyTorch
Where the posting names them
- Bachelor’s degree in computer science, electrical and computer engineering, data science, statistics, biomedical engineering, mechanical engineering, operations research, robotics, computational neuroscience, applied mathematics, physics, or a closely-related discipline and five years of related work experience. Master’s or PhD is preferred. - Experience with the Linux operating system and utilizing the command line interface. ● Demonstrated ability and experience with scripting and programming languages (Bash, Python). - Hands-on experience with shared high-performance computing environments and workload scheduling tools (e.g., SLURM).
Preferred Qualifications: - Experience with parallel computing, GPU operation (CUDA Toolkit), multi-GPU training, and distributed frameworks for machine learning (e.g. PyTorch Distributed). - Prior software engineering experience within AI, scientific computing, or robotics domains in industry, academia, government, or non-profit organizations, which involved architecting and managing codebases for large-scale technical projects
Your next step
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Already applied? Track this application
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Research Software Engineer, UD Institute for Data Science
Apply now
Job no: 503750
College / VP Area: Research Office
Work type: Staff
Location: Newark, DE
Categories: Research & Laboratory
Pay Grade: 31S
Context of Job:
The University of Delaware (UD) invites applications for a Research Software Engineer (RSE) to join the NSF AI Institute for Human-AI Cooperation (HAIC). The HAIC Institute (https://haicinstitute.org/) is a 5-year (2026-2031), $21.5 million, multi-institutional research initiative supported by the National Science Foundation. HAIC brings together researchers and partners to develop trustworthy AI that strengthens human expertise, shapes the future of rehabilitation and health care, and cultivates the next generation of leaders in AI. The RSE will work with HAIC researchers (from UD, University of Florida, University of Pennsylvania,Princeton University and other partner institutes) to build, validate, and maintain robust and scalable open-source software tools and cyberinfrastructure that support institute-wide research in artificial intelligence (including reinforcement learning and large vision-language models), biophysical digital twins, multimodal data processing, personalized rehabilitation, and human-AI symbiosis. The RSE will leverage high-performance computing (HPC) systems including University of Florida’s HiPerGator NVIDIA SuperPod and NSF funded NAIRR resources, and work extensively with research computing professionals and NVIDIA systems engineers. Software needs include supporting reproducible research, interfacing with real-time systems and databases, and translation of AI models for a variety of deployment settings. The RSE will join a growing cohort of RSE at UD, with coordinated professional development opportunities.
This position is supported by the U.S. National Science Foundation through U.S. National Science Foundation under Cooperative Agreement No. 2433450. Continuation of this position is contingent upon performance and continued availability of these funds. Notice of non-renewal is not required.
This position is supported by the U.S. National Science Foundation through U.S. National Science Foundation under Cooperative Agreement No. 2433450. Continuation of this position is contingent upon performance and continued availability of these funds. Notice of non-renewal is not required.
Major Responsibilities
- Participate as a member of a highly technical, research driven team, forging close working relationships with HAIC researchers (faculty, post-doctoral, students, and staff) across multidisciplinary working groups.
- Provide support to HAIC researchers to use research computing hardware and software for workflows involving AI, data science, machine learning, and physics simulation, especially machine learning frameworks with interfaces for monitoring training, robust checkpointing, and validation suites.
-
Assist researchers to develop, deploy, scale, and optimize workflows that effectively and efficiently use these high-performance computing resources.
-
Utilize industry standard research software practices such as establish software version control, pipelines, institute standard testing frameworks, maintain documentation, manage public GitHub repositories to support research dissemination, applying best practices when authoring and assisting in the pursuit of modular and maintainable software codebases that accelerate scientific discovery and societal impact.
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Help to identify appropriate hardware, software, and cyberinfrastructure platforms for different stages of research and development, including data collection, storage, and integration, along with computational-focused education and workforce development activities, assist in procurement, set-up, testing, and documentation.
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Enable the translation of software and models toward deployment in various settings and platforms.
-
Serve as a computational liaison to research computing and IT groups at UD and partner institutions.
-
Educate, train, and advise both novice and experienced researchers regarding software engineering, shared high performance computing environments, associated software and services—adapting to individual needs and experiences—and assist in the development of workshops and other training resources.
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Work proactively to broaden engagement between HAIC and the research cyberinfrastructure user community.
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Perform other related duties as assigned.
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Maintain knowledge of applicable laws and developments in state-of-the-art technology, equipment, and systems to support the institute projects.
Possible Project-Specific Technical Responsibilities:
- Biophysical Modeling & Omniverse Integration: Assist in the development and translation of biophysical, kinematic, and musculoskeletal models (e.g., OpenSim, MuJoCo) into the NVIDIA Omniverse environment to support dynamic digital twin simulations.
- Multimodal Data & Sensor Fusion: Implement or accelerate processing and inference algorithms for real-time multimodal data, natural language, signal, and image processing.
- Integration of Large Language Models with Knowledge Retrieval: Assist in the use and integration of APIs, open-weight models, etc. combined with large graph databases.
Qualifications
- Bachelor’s degree in computer science, electrical and computer engineering, data science, statistics, biomedical engineering, mechanical engineering, operations research, robotics, computational neuroscience, applied mathematics, physics, or a closely-related discipline and five years of related work experience. Master’s or PhD is preferred.
- Experience with the Linux operating system and utilizing the command line interface.
● Demonstrated ability and experience with scripting and programming languages (Bash, Python). - Hands-on experience with shared high-performance computing environments and workload scheduling tools (e.g., SLURM).
- Extensive experience with version control and git, with contributions to open source repositories.
- Ability to work effectively with researchers (both computational and non-computational) within multi-institutional teams to define, clarify, and execute requirements and goals.
- Excellent oral and written communication skills.
- Ability to manage multiple projects, keeping oriented to the goals and tracking details, efficiently communicating on issues and outcomes, and executing independently and in collaboration.
- Effective organizational, interpersonal, and customer-service skills.
- Aptitude for learning quickly and functioning in a dynamic technological environment.
Preferred Qualifications:
- Experience with parallel computing, GPU operation (CUDA Toolkit), multi-GPU training, and distributed frameworks for machine learning (e.g. PyTorch Distributed).
- Prior software engineering experience within AI, scientific computing, or robotics domains in industry, academia, government, or non-profit organizations, which involved architecting and managing codebases for large-scale technical projects
- Prior contribution to computationally-focused research publications and/or software, or contribution to creating developer documentation, API guides, and descriptions of software use cases or other write-ups.
- Experience with modern collaborative productivity environments (e.g., Slack, Trello, etc.).
- Experience utilizing AI-assisted programming environments (e.g., GitHub Copilot, Codex, Cursor, or LLM-driven coding tools) to streamline software development, unit testing, and refactoring.
- Course work or experience in one or more areas: AI, data science, machine learning, computer vision, signal processing, knowledge representation (e.g., knowledge graphs), information retrieval, statistics, biophysical modeling, robotics, or neuroengineering.
- Experience developing within NVIDIA Omniverse, Isaac Sim, Isaac Gym, or custom CUDA kernels.
Notice of Non-Discrimination and Equal Opportunity
The University of Delaware does not discriminate against any person on the basis of race, color, national origin, sex, gender identity or expression, sexual orientation, genetic information, marital status, disability, religion, age, veteran status or any other characteristic protected by applicable law in its employment, educational programs and activities, admissions policies, and scholarship and loan programs as required by Title IX of the Educational Amendments of 1972, the Americans with Disabilities Act of 1990, Section 504 of the Rehabilitation Act of 1973, Title VI and VII of the Civil Rights Act of 1964, and other applicable statutes and University policies. The University of Delaware also prohibits unlawful harassment including sexual harassment and sexual violence.
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Newark, DE
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