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About This Role
Job Description:
The School of Engineering at Brown University has a new and exciting opportunity to hire a Research Engineer.
The Research Engineer is responsible for the design, fabrication, purchasing, and maintenance of laboratory equipment and facilities surrounding projects related to experimental fluid mechanics. The incumbent will provide support related to the preparation of posters, publications, and progress reports; may participate in the writing and preparation of proposals for research grants and sponsored funding. They will provide general laboratory support including upkeep and maintenance of fabrication equipment (3D printers, laser cutter, laser engraver, benchtop CNC, hand tools, bench tools) and assisting users with the devices and providing design guidance and fabrication support. Maintain and improve lab organization system. They will also serve as lab liaison to the Brown Design Workshop, IT, Facilities, and Environmental Health & Safety.
This is a part-time, 15 hour per week, one-year, fixed term position. Effort and position end date can be increased/extended upon the continued availability of funding and research needs.
Brown University provides equal opportunity and prohibits discrimination, harassment and retaliation based upon a person’s race, color, religion, sex, age, national or ethnic origin, disability, veteran status, sexual orientation, gender identity, gender expression, or any other characteristic protected under applicable law, in the administration of its policies, programs, and activities. The University recognizes and rewards individuals on the basis of qualifications and performance.
The successful candidate, as a minimum, should have the following background:
Education and Experience
Bachelor’s degree in Engineering or related discipline.
1-2 years experience with engineering design and design project experience.
Experience in a university laboratory setting is preferred.
Job Competencies
Experience in CAD, rapid-prototyping techniques, metal and woodworking, and circuit design.
Software experience with Python and MATLAB, and experience with Arduino, ESP32, and Raspberry Pi hardware.
Excellent customer service orientation and communication skills, both verbal and written to communicate technical and design issues and ideas clearly.
Demonstrated ability to support a community of diverse perspectives and cultures in an inclusive environment.
Initiative and ability to work independently and as a member of a team.
Please submit a cover letter, specifying which position you are applying to and a resume with your application.
All offers of employment are contingent upon a criminal background check and education verification satisfactory to Brown University.
For current information on Brown's vaccine requirements and other community health matters, please refer to the Healthy Brown website.
Why Brown?
Brown University is a leading research university that is distinct for its student-centered learning and deep sense of purpose. Our students, faculty, and staff are driven by the idea that their work will impact the world.
Brown University offers a flexible work/life balance, summer hours, winter break, and a comprehensive Benefits package, including time off and annual paid holidays. Benefit offerings include health, dental, vision, tuition assistance, retirement, wellness, employee discounts, and more.
Benefits of Working at Brown:
Please review additional information on the Benefits of Working at Brown.
Recruiting Start Date:
2026-10-01Job Posting Title:
Research EngineerDepartment:
School of EngineeringGrade:
Grade 9Worker Type:
EmployeeWorker Sub-Type:
Fixed Term (Fixed Term)Time Type:
Part timeScheduled Weekly Hours:
15Position Work Location:
Onsite Submission Guidelines:
The designated Position Work Location for each position determines the approved modality of work. Positions are classified based on the operational and business needs of the department and may be designated as on-site, hybrid, or remote.
Employees with a designated position work location as remote must reside and perform their work in a state where Brown University is registered to do business. Brown University is a registered employer in the following states: Rhode Island, California, Colorado, Connecticut, Florida, Maryland, Massachusetts, New York, New Hampshire, New Jersey, North Carolina, Washington, D.C.
Please note that to be considered for a staff position at Brown University, you must submit a separate application for each position you wish to be considered for. Applications are reviewed only for the specific position to which they are submitted and are not automatically considered for future openings.
This position is not eligible for visa sponsorship.
Still Have Questions?
If you have any questions you may contact [email protected].
Brown is an E-Verify Employer.
EEO Statement:
Brown University provides equal opportunity and prohibits discrimination, harassment and retaliation based upon a person’s race, color, religion, sex, age, national or ethnic origin, disability, veteran status, sexual orientation, gender identity, gender expression, or any other characteristic protected under applicable law, in the administration of its policies, programs, and activities. The University recognizes and rewards individuals on the basis of qualifications and performance. The University maintains certain affirmative action programs in compliance with applicable law.
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 Brown 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 $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.
Brown University AI Hiring
Brown University has 1 open AI role right now. They're hiring across Research Engineer. Based in Providence, RI, US.
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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