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About This Role
Research Engineer – Software Developer
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Job No: 26142
Department: Michigan Tech Rsrch Institute(MTRI)
Work Type: Staff \- Full Time
Location: Michigan Tech Research Institute (Ann Arbor, MI)
Full Time / Part Time: Full Time
Categories: Engineering, Research
Applications Close:
Michigan Technological University is an R1 technological research university founded in 1885 in Houghton. Our rural campus is situated just miles from Lake Superior in Michigan's scenic Upper Peninsula and is home to nearly 7,500 students from more than 60 countries around the world. Consistently ranked among the best universities in the country for return on investment, Michigan’s flagship technological university offers more than 185 undergraduate and graduate degree programs. Research focus areas include defense, health, energy, automotive, environment, and aerospace.
The area’s waters, forests, and snowfall support year\-round recreation, including skiing, snowboarding, hiking, biking, and paddling. The University is an integral part of the region, supported by a friendly and welcoming community that takes pride in being a true college town. We embrace our size, climate, sense of adventure, and originality.
Summary
Michigan Tech Research Institute is seeking an entry \- to mid \- level software developer to help support variety of scientific and research programs for our government and commercial customers. The successful candidate will have a solid background in computer science with strong skills in software prototyping, software design, and deployment. The position is on\-site, located at MTRI in Ann Arbor, MI (www.mtri.org).
Responsibilities and Essential Duties
1\. Design and develop software user interfaces; design methodologies and toolsets; design and conduct tests.
2\. Support data management for remote sensing projects through the design and maintenance of scientific databases.
3\. Develop software to prototype and evaluate signal processing, remote sensing, and/or machine learning algorithms.
4\. Assist with defining software objectives by analyzing user requirements, system features, and functionality.
5\. Recommend software solutions by comparing pros and cons of custom versus off\-the\-shelf alternatives.
6\. Coordinate requirements and schedules, contribute to team meetings, troubleshoot development and production problems.
7\. Develop software documentation and assistance tools.
8\. Continue to improve performance by being aware of new technologies and software products, participating in educational opportunities, reading professional publications, and participating in professional organizations.
9\. Accept ownership of, and responsibility for responding to new and varied requests.
10\. Apply safety\-related knowledge, skills, and practices to everyday work.
11\. Commit to learning about continuous improvement strategies and applying them to everyday work. Actively engage in University continuous improvement initiatives.
Required Education, Certifications, Licensures
Bachelor’s degree in computer science, mathematics, or engineering with computer science experience.
Required Experience
1\. Strong programming skills with experience in one or more of the following programming languages/software: Python, MATLAB, C\+\+, or equivalent.
2\. Coursework or experience using software development tools, including revision control systems, containerization, and virtual environments.
3\. Demonstrated organizational ability and attention to detail.
4\. Demonstrated ability to participate in team projects.
5\. Familiarity with Linux or other Unix\-based operating system.
Desirable Education and/or Experience
1\. Master’s degree in a related field with 2 years of relevant work experience or Bachelor’s degree with 5 years of relevant work experience.
2\. Experience with image processing, sensors, and/or signal processing.
3\. Basic knowledge of one or more of the following: statistics, database design and maintenance, UI design and development, CI/CD pipelines, ROS (Robotic Operating System), geospatial data formats and processing (GDAL or similar), command line Unix tools.
4\. Experience working with multidisciplinary teams to perform research, solve technical problems, and/or develop software tools.
5\. Experience using cloud\-based computing systems.
6\. Experience leading software development tasks and coordinating teams of junior software developers.
Required Knowledge, Skills, and/or Abilities
1\. Ability and willingness to obtain a Department of Defense security clearance, which requires United States citizenship. Obtaining a national security clearance while holding a dual citizenship will not be possible when the foreign country poses a risk to the national security of the United States.
2\. Excellent interpersonal, oral, and written communication skills.
3\. Ability to take direction, but work without continuous oversight.
4\. Ability to exercise discretion and independent judgement with respect to significant matters related to job duties.
5\. Demonstrated ability to participate in team projects.
6\. Demonstrated commitment to contribute to a safe work environment.
Desirable Knowledge, Skills, and/or Abilities
1\. Holds active Department of Defense security clearance.
2\. Ability to clearly communicate complex ideas at meetings and symposia.
3\. Ability to contribute to competitive grant proposals.
4\. Ability to develop software without use of AI\-assisted coding tools.
Work Environment and/or Physical Demands
WORK ENVIRONMENT: The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
The noise level in the work environment is usually low to moderate.
Required Training and Other Conditions of Employment
Every employee at Michigan Technological University will receive the following training courses:
- Employee Safety Overview
- Annual Data Security Training
- Anti\-Harassment, Discrimination, Retaliation Training
- Annual Title IX Training
Additional training will be required by the department on a periodic basis.
Background Check:
Offers of employment are contingent upon and not considered finalized until the required background check has been performed and the results received and assessed.
Full\-Time Equivalent (FTE) % (1\=100%)
1
FLSA Status
Exempt
Appointment Term
12 months
Shift
*
Pay Rate/Salary
Negotiable based on experience.
Title of Position Supervisor
Research Engineer III
Posting Type
Internal \& External
Dependent on Funding
Yes
Additional Information
This position is contingent upon the continued availability of external funding.
*To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.*
*If you require any auxiliary aids, services, or accommodations during Michigan Tech’s hiring process please notify the Human Resources office at 906\-487\-2280 or hr\[email protected].*
*Other Conditions of Employment:*
*Please note that successful applicants are responsible for ensuring their eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without the need of an employer sponsorship) on or before the effective date of your appointment, and maintain eligibility without sponsorship throughout your appointment.*
*Michigan Technological University is an Equal Opportunity Educational Institution/Equal Opportunity Employer that provides equal opportunity for all, including protected veterans and individuals with disabilities.*
*The* *Annual Security and Fire Safety Report* *contains current campus safety and disciplinary policies, crime statistics for the previous 3 calendar years, and on\-campus student housing fire safety policies and fire statistics for the previous 3 calendar years. Michigan Tech will provide a paper copy upon request; please contact the Michigan Tech Public Safety.*
*In compliance with the federal Drug\-Free Schools and Communities Act (DFSCA) and its implementing regulations (34 CFR Part 86\), Michigan Tech is committed to maintaining a drugfree campus environment and actively promoting the health and safety of its community. Find* *our notice* *that outlines the University's policies, legal sanctions, health risks, and available support resources related to the unlawful possession, use, or distribution of illicit drugs and alcohol.*
Required Education, Certifications, Licensures\* (minimum requirements)
Advertised: 12 Aug 2026 Eastern Daylight Time
Applications Close:
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 4,317 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Michigan Technological University, 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 $272,100 based on 227 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and AI Engineering Manager ($244,000). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Michigan Technological University AI Hiring
Michigan Technological University has 1 open AI role right now. They're hiring across Research Engineer. Based in Ann Arbor, MI, US.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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