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GENERAL SUMMARY
Under general administrative and technical direction from the Vice President of Research and Laboratory Services, develops and acquires research programs and conducts asphalt mixtures research as contracted by private and public organizations. Promotes and acquires mixture performance testing projects and forensic analyses for private and public entities. Collaborates with leadership, laboratory, and engineering staff on research and testing projects, as appropriate. Conducts, within budget constraints, internal research on timely technical matters of importance to the Asphalt Institute and its member companies. Provides direction to laboratory technicians and interns in the execution of the above activities. Prepares research reports and presents findings at technical venues. Prepares technical papers for peer reviewed publications. Assists with on-site and off-site lab training and certification programs involving asphalt mixture testing. Provides technical support to members and other Asphalt Institute divisions as needed.
ESSENTIAL JOB FUNCTIONS
Conducts the following activities under general administrative and technical direction from the VP of Research and Laboratory Services:
- Assists the VP of Research and Laboratory Services in maintaining a viable asphalt mixtures research and testing program to advance the goals of the Asphalt Institute. Actively pursues and acquires relevant research opportunities, primarily in asphalt mixtures and performance testing, and works with other research entities and individuals to collaborate on the same research initiatives.
- Develops and conducts research and testing projects. Oversees and conducts (as needed) laboratory testing with an emphasis on performance-related tests. Analyzes test results and writes laboratory testing reports and research reports. Adheres to, supports, and delivers project timelines and deadlines for all the above.
- Manages laboratory specialists and interns in the Mixtures Performance Lab on testing and research projects, including coordination and delegation of tasks. Provides input on performance evaluations.
- Composes research reports, presents and publishes research findings in technical journals, proceedings, and trade publications.
- Participates and assumes leadership positions in professional industry organizations – such as Transportation Research Board (TRB) and Association of Asphalt Paving Technologists (AAPT) – including presenting research findings. Maintains an effective depth of knowledge related to the most current asphalt technology.
- Assists the VP of Research and Laboratory Services in the performance of some administrative functions such as preparing budgets and reviewing laboratory financial statements to ensure compliance with objectives.
- Collaborates with Asphalt Institute Regional Engineers and the VP of Engineering by providing technical support to members, user agencies, and other industry partners as required.
The intent of this job description is to provide a representative summary of the major duties and responsibilities of this position. Incumbents may be requested to perform job-related tasks other than those specifically presented in this description.
KNOWLEDGE AND ABILITIES
Minimum requirement of a Bachelor’s degree in Civil Engineering or a related field of study. Higher level of education (Master’s degree or PhD) preferred. Professional Engineer (PE) license is required. Active membership in one or more related professional organizations is desirable. Knowledge of asphalt paving material composition, design and construction practices, pavement behavior and evaluation, laboratory testing procedures and equipment, and statistical analysis techniques – including statistical design of experiments – is required.
Must have demonstrated skills to successfully develop, initiate, and complete research projects and programs. Demonstrated project management skills required. Must be proficient in the use of standard information technology platforms. Excellent interpersonal, written, oral communication, and organizational skills required. Must obtain and maintain a valid U.S. driver's license.
EXPERIENCE
A minimum of eight (8) years of postgraduate experience in asphalt materials testing, characterization, and analyses is required.
OTHER REQUIREMENTS AND CONDITIONS
Position has no unusual physical demands; however, it may require commercial airline and automobile travel principally within the U.S. and Canada. Travel is expected to be 25% of the time or less. International travel outside of North America is not expected.
Consistent, timely attendance is a requirement to maintain compliance with Asphalt Institute policy. The position may involve exposure to potential hazards of laboratory chemicals and testing equipment.
Pay: $115,000.00 - $125,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Flexible spending account
- Health insurance
- Paid time off
- Vision insurance
Work Location: In person
Salary Context
This $115K-$125K range is in the lower quartile for Research Engineer roles in our dataset (median: $191K across 47 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 8,943 AI roles we're tracking, Research Engineer positions make up 3% of the market. At Asphalt Institute, 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 419 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($120K) sits 52% below the category median. Disclosed range: $115K to $125K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and AI Engineering Manager ($251,622). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Asphalt Institute AI Hiring
Asphalt Institute has 1 open AI role right now. They're hiring across Research Engineer. Based in Lexington, KY, US. Compensation range: $125K - $125K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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