Interested in this Research Engineer role at University of Alabama?
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- Tuscaloosa, Alabama, United States
- Engineering/Computer Science
- Research/Scientific
- Closing at: Oct 31 2026 - 22:55 CDT
Pay Grade/Pay Range: Minimum: $57,200 - Midpoint: $74,300 (Salaried E9)
Department/Organization: 214251 - Electrical and Computer Eng
Normal Work Schedule: Monday - Friday 8:00am to 5:00pm
Job Summary: The Research Engineer uses fundamental concepts, practices, and procedures of a particular field of specialization to perform varied scientific research requiring application and adaptation of established techniques, procedures, and criteria. Evaluates, selects, and applies standard scientific techniques, procedures, and criteria to accomplish a variety of research assignments. Performs various research projects to include conducting experiments, writing research proposals, writing technical papers and research reports.
Additional Department Summary: Develops a system that includes hardware and control and management algorithms programing/software. The position will be developing, testing, and demonstrating power electronic systems hardware with power converters each with power levels that exceed 10 kW and/or voltages of up to 1000 V, advanced control of power electronic systems, analog-digital mixed power controllers for power electronic systems, electric vehicles fast chargers, and Lithium-Ion battery energy storage, but is subject to change.
Works on developing and testing/validating this system, use and maintain laboratory and its electrical and mechanical equipment and tools, prepare/write reports, and assist in lab management, maintenance and safety, etc. Laboratory safety responsibilities will include safe storage, use and disposal of batteries and other material, and providing safety supervision to users.
Required Minimum Qualifications: Bachelor's degree and two (2) years of research experience; OR master's degree and some research experience.
Skills and Knowledge: Knowledge in developing, testing, and demonstrating power electronic systems hardware with power converters each with power levels that exceed 10 kW and/or voltages of up to 1000 V, advanced control of power electronic systems, analog-digital mixed power controllers for power electronic systems, electric vehicles fast chargers, and Lithium-Ion battery energy storage. Excellent electrical and good mechanical skills. Ability to work collaboratively with faculty, staff, and students. Must be willing and able to learn additional skills that are needed for the project and remain proficient and up to date with the state-of-the-art technology to support the project. Knowledge in Artificial Intelligence (AI)/Machine Learning algorithms and hardware is preferred
Preferred Qualifications: Significant experience in one or more of the technical or research areas related to the project.
Experience with artificial intelligence and machine learning methods for energy systems, including data-driven modeling, real-time inference, and adaptive control. Familiarity with AI model training, validation, and deployment on embedded or edge platforms. Knowledge of data integrity, robustness, and basic cybersecurity considerations in AI-enabled control systems is a plus.
Must be willing and able to learn additional skills that are needed for the project and remain proficient and up to date with the state-of-the-art technology to support the project. The position continuity is subject to availability/continuity of external funding for the project.
Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre-employment background investigation and information obtained from social media and other internet sources. A prior conviction reported as a result of the background investigation DOES NOT automatically disqualify a candidate from consideration for this position. A candidate with a prior conviction or negative behavioral red flags will receive an individualized review of the prior conviction or negative behavioral red flags before a hiring decision is made.
Equal Employment Opportunity: The University of Alabama is an Equal Employment/Equal Educational Opportunity Institution. All qualified applicants will receive consideration for employment or volunteer status without regard to any legally protected basis and will not be discriminated against because of their protected status. Applicants and employees of this institution are protected under Federal law from discrimination on several bases. More information is available in the EEOC’s Know Your Rights: Workplace discrimination is illegal poster.
The University of Alabama affirms its longstanding commitment to institutional neutrality, free speech, and academic freedom.
Salary Context
This $57K-$74K range is in the lower quartile for Research Engineer roles in our dataset (median: $165K across 57 roles with salary data).
View full Research Engineer salary data →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 Alabama, 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 in Demand for This Role
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. This role's midpoint ($65K) sits 74% below the category median. Disclosed range: $57K to $74K.
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 Alabama AI Hiring
University of Alabama has 1 open AI role right now. They're hiring across Research Engineer. Based in Tuscaloosa, AL, US. Compensation range: $74K - $74K.
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.
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