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About This Role
Required
- A BA/BS degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, Physics, or a closely related field, or a combination of education and relevant work experience to equal at least four years.
- Academic or professional experience with basic Internet of Things (IoT) hardware or embedded prototyping.
- Exposure to low-level programming/firmware (e.g., Embedded C/C++) or scripting languages (e.g., Python, Matlab, or R).
- Basic familiarity with computer-aided design (CAD) software (e.g., Solidworks, Autodesk360) or PCB layout tools (e.g., Altium, Eagle).
- Demonstrated ability to follow detailed protocols and execute recurring tasks with precision and timeliness, working collaboratively in an interdisciplinary team of engineers, data scientists, and non-engineers.
Preferred
- Coursework or additional education in Electrical Engineering, Mechanical Engineering, Computer Engineering, or a closely related field
- Hands-on experience (coursework, projects, or work) building Internet of Things (IoT) prototypes for sensing, instrumentation, robotics, or wireless connectivity, such as low-power embedded systems, power electronics, analog signal chains, or printed circuit boards
- Exposure to hardware and firmware tools such as embedded C/C++, Eagle, Altium, Xilinx, Solidworks, or Autodesk360, including troubleshooting existing hardware and firmware and operating 3D printers
- Experience programming in Python, Matlab, or R; use of GitHub and the Particle IoT platform; exposure to Markdown, HTML, or LaTeX
- Work, project, or field experience with sensing, instrumentation, robotics, advanced manufacturing, or wireless connectivity, including deploying or maintaining sensors outdoors or in low-connectivity settings
- Familiarity with the stages of a hardware system life cycle (specification, design, prototyping, manufacturing, quality assurance, deployment, maintenance, decommissioning) and with the IoT stack from sensing to wireless backhaul, web servers, databases, and front-end applications
- Willingness to travel occasionally, primarily day trips to field sites
Department: CFANS GEMS Informatics Center
Supervisor: Bryan Runck, PI Real-time GeoInformation Systems Lab
Location: 248 Ruttan Hall and 305 Cargill, St. Paul Campus
We seek a highly motivated multidisciplinary engineer to serve in the Runck Lab in the GEMS Informatics Center. The successful candidate will support research in instrumentation and internet of things systems and will support the GEMS Sensing Service Organization.
Description:
This is a 100% research position with the primary aim of prototyping and supporting existing distributed, low cost electronics systems. Work is performed under general supervision, following established lab procedures and guidelines.
- Research and Development (70%) + Sensing & Instrumentation: Assist in assembling, soldering, testing, and debugging low-power embedded hardware and sensor systems. + Prototyping & Manufacturing: Print CAD models/components using 3D printers and assist in assembling prototype Printed Circuit Boards (PCBs). + Software & Connectivity: Write scripts (Python, Matlab, R, Embedded C/C++) to assist with data processing, basic firmware development, and data extraction/ingestion into lab databases. + Testing & Evaluation: Assist with gathering basic user feedback, administering standardized user surveys, and supporting design review meetings. + Documentation & Reporting: Contribute to research documentation, including assisting with standard operating procedures (SOPs), training tutorials, lab wikis, and drafting technical sections of research reports or manuscripts. + Field Support: Assist the Lab Field Manager with standard setup, maintenance, and basic troubleshooting of field-deployed sensing units.
- Research support (20%) + Support workspace operations by adhering to quality standards and maintaining experimental stations in a clean, organized manner. + Execute routine lab maintenance tasks, including restocking consumables, maintaining 3D printer performance, and performing basic hardware/tool setup under direction. + Assist with placing equipment/component orders by requesting vendor quotes under supervisor direction. + Guide student workers on proper lab cleanup, safety procedures, and basic tool usage.
- Education and Training (10%) + Assist in preparing basic instructional materials and demonstrations for online or face-to-face learning modules. + Help facilitate routine hands-on training sessions on basic IoT and sensor technology for undergraduate students, K-12 groups, or workshop attendees.
The Runck Lab focuses on the science and engineering of real-time geoinformation systems ranging from data collection (hardware, firmware) through to data storage, modeling, and visualization. On-going work focuses on the application of novel spatial machine learning and artificial intelligence models in real-time to support decision-making, the development of novel sensing modalities, and the effects of geovisualization systems on cross-organization decision-making and action.
Funding for the lab comes from diverse sources including recurring funding through the GEMS Informatics Center from the MnDRIVE program, federal grants, state grants, foundations, and private companies. The lab fluctuates between 8 and 12 members with two full-time research staff supporting lab operations and GEMS Sensing, a service organization focused on research support for environmental data collection. Due to the applied and cross-sector nature of R&D, the lab provides an opportunity to broadly engage in large, multidisciplinary, and high impact R&D.
The GEMS Informatics Center is a joint initiative of the College of Food, Agriculture and Natural Resource Sciences and the Minnesota Supercomputing Institute and is a highly diverse international and interdisciplinary team of professionals. The Center is re-imagining the relationships between data, institutions, and disciplines to inform and accelerate innovation within the food and agricultural sectors. GEMS broadly seeks to make genomics, environmental, management, and socioeconomic data inter-operable at varying spatial and temporal scales to generate actionable information and promote new innovation partnerships that accelerates and sustains growth in local and global food and agricultural systems.
Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will be given the opportunity to complete an online application for the position and attach a cover letter and resume.
Additional documents may be attached after application by accessing your "My Job Applications" page and uploading documents in the "My Cover Letters and Attachments" section.
To request an accommodation during the application process, please e-mail [email protected].
The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.
The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu
Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.
The University of Minnesota, Twin Cities (UMTC)
The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation's most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.
At the University of Minnesota, we are proud to be recognized by Forbes as a Best Employer for Company Culture (2026), Best Employer for Women (2023, 2025, 2026), and Best Employer by State (2022-2026). In 2026, we also received Culture Excellence & Industry Awards recognition for employee appreciation and work-life flexibility.
Role Details
About This Role
Research Engineers bridge the gap between research and production. They implement papers, build experiment infrastructure, optimize training pipelines, and make research prototypes production-ready. They're the engineers who make research work at scale.
The role sits at a unique intersection. You need to understand the math well enough to implement novel architectures correctly, and you need the engineering chops to make them run efficiently on distributed systems. When a research scientist has a breakthrough idea, you're the person who turns it from a notebook prototype into a training pipeline that runs on 256 GPUs.
Across the 9,079 AI roles we're tracking, Research Engineer positions make up 2% of the market. At University of Minnesota, this role fits into their broader AI and engineering organization.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
What the Work Looks Like
A typical week involves: implementing a new attention mechanism from a recent paper, profiling and optimizing a training pipeline that's bottlenecked on data loading, building evaluation infrastructure for a new benchmark, debugging distributed training issues across a GPU cluster, and pair-programming with a research scientist on their latest experiment. The work is deeply technical.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
Skills Required
Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.
Experience with large-scale training infrastructure (FSDP, DeepSpeed, Megatron), GPU programming (CUDA, Triton), and the internals of ML frameworks (PyTorch internals, custom autograd functions) is what makes candidates stand out. The best research engineers can debug issues that span the full stack from GPU memory management to numerical precision to algorithmic correctness.
Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
Compensation Benchmarks
Research Engineer roles pay a median of $252,000 based on 457 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and AI Engineering Manager ($251,622). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
University of Minnesota AI Hiring
University of Minnesota has 2 open AI roles right now. They're hiring across Research Engineer, AI/ML Engineer. Positions span Minneapolis, MN, US, Minneapolis, MN.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into Research Engineer roles include Software Engineer, ML Engineer, Research Intern.
From here, career progression typically leads toward Senior Research Engineer, Research Scientist, ML Architect.
This is one of the best entry points into AI research without a PhD. Build a strong engineering portfolio with ML projects, contribute to open-source ML frameworks, and demonstrate that you can implement complex ideas correctly and efficiently. The transition to Research Scientist is possible with published first-author work, which some research engineer roles support.
What to Expect in Interviews
Technical screens test both engineering skill and research understanding. Expect coding rounds with performance-critical implementations (GPU optimization, efficient data loading). Be prepared to discuss papers relevant to the team's research area and explain how you'd implement key ideas. System design questions focus on training infrastructure: distributed training, experiment tracking, and compute resource management.
When evaluating opportunities: Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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