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About This Role
Research Engineer III
-------------------------
Job No: 26119
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: 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
MTRI is seeking a motivated professional to help support multiple projects for our government and commercial customers. The Software Developer will work with senior engineers and scientists to research, develop, and evaluate algorithms for a variety of signal and/or image processing applications. 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\. Participate as an integral team member on multi\-disciplinary research relating to applying technological skills to solving governmental and societal needs.
2\. Provide technical, analytical and numerical support for research and development projects in the areas of mathematics, statistics, programming, electrical engineering, remote sensing, and signal
processing.
3\. Lead software development projects and coordinate teams of junior software developers.
4\. Develop software to prototype and evaluate signal processing, remote sensing, and/or machine learning algorithms.
5\. Assist with defining software objectives by analyzing user requirements, system features, and functionality.
6\. Recommend software solutions by comparing the pros and cons of custom versus off\-the\-shelf alternatives.
7\. Coordinate requirements and schedules, contribute to team meetings, troubleshoot development and production problems.
8\. Develop software documentation and assistance tools.
9\. 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.
10\. Accept ownership of, and responsibility for responding to, new and varied requests.
11\. Assist research staff with deployment of cloud computing architectures for data processing.
12\. Apply safety\-related knowledge, skills, and practices to everyday work. Apply safety\-related knowledge, skills, and practices to everyday work.
Required Education, Certifications, Licensures
- Master’s degree or higher in computer science, computer engineering, mathematics, electrical engineering, or a similar related field, and 5 years of professional software development experience
OR
- Bachelor’s degree in computer science, computer engineering, mathematics, geospatial data science, electrical engineering, or a similar related field, and 8 years professional software development experience
Required Experience
1\. Experience in the design, implementation, and evaluation of algorithms.
2\. Professional experience in software development.
3\. Proficiency in at least one of the following: Python, C\+\+, MATLAB,
4\. Proficient in at least three of the following: applied mathematics, physics, electrical engineering, software design, signal processing, image processing, machine learning, reinforcement learning, numerical analysis, statistics, robotics, or distributed computing.
5\. Proficient in Linux or other Unix\-based operating system.
6\. Experience leading software development teams.
Desirable Education and/or Experience
1\. Experience in or coursework covering geospatial data or image processing.
2\. Experience with sensors or signal processing.
3\. Experience with one or more of the following: database design and maintenance, CI/CD pipelines, ROS (Robotic Operating System), geospatial data processing (GDAL or similar),
4\. Experience working with multidisciplinary teams to perform research, solve technical problems, and/or develop software tools.
5\. Experience with the deployment of cloud\-based computing architectures.
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/written, and presentation communication skills.
3\. Demonstrated ability to participate in team projects.
4\. 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.
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 4 required trainings; additional training may be required by the department.
Required University Training:
- Employee Safety Overview
- Anti\-Harassment, Discrimination, Retaliation Training
- Annual Data Security Training
- Annual Title IX Training
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 and 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: 14 Jul 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 3,708 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 $280,000 based on 147 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and AI Architect ($254,798). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
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, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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