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How much do artificial intelligence research engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for artificial intelligence research engineer in the United States is $106,012.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $104,000.00 per year, depending on experience, location, and employer.

What is an artificial intelligence research engineer?

Artificial Intelligence (AI) Research Engineers are professionals who design, develop, and implement cutting-edge AI algorithms and models. They work at the intersection of computer science, mathematics, and data science to solve complex problems using machine learning, deep learning, and other AI technologies. Their responsibilities often include researching new AI techniques, publishing findings, and collaborating with cross-functional teams to turn theoretical advancements into practical applications. These engineers play a crucial role in driving innovation across industries such as healthcare, finance, and robotics.

What are some common challenges artificial intelligence research engineers face when transitioning from academic research to industry roles?

Artificial Intelligence Research Engineers often find that moving from academic research to industry requires adapting to faster development cycles and a stronger focus on practical, scalable solutions. In industry, there's typically a greater emphasis on collaboration with cross-functional teams, integrating research into real-world products, and aligning work with business goals. Balancing innovative research with production deadlines can be challenging but also offers opportunities to see your ideas make tangible impact. Building strong communication skills and learning to prioritize projects are key to thriving in this environment.

What are the key skills and qualifications needed to thrive as an artificial intelligence research engineer, and why are they important?

To thrive as an Artificial Intelligence Research Engineer, you need a strong background in computer science, mathematics, and machine learning, typically supported by an advanced degree in a related field. Familiarity with programming languages like Python, frameworks such as TensorFlow or PyTorch, and experience with cloud computing platforms are essential technical qualifications. Critical thinking, creativity, and effective communication are standout soft skills for this role. These abilities are crucial for developing innovative AI solutions, collaborating with interdisciplinary teams, and advancing research in a rapidly evolving field.

What are popular job titles related to Artificial Intelligence Research Engineer jobs?

For Artificial Intelligence Research Engineer jobs, the most frequently searched job titles are:

Artificial Intelligence Research Engineer jobs near you
Infographic showing various Artificial Intelligence Research Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $106,012 per year, or $51 per hour.

Talent Intelligence Research Engineer

Alexandria, VA • On-site

McChrystal Group
Business Management Consulting • 51 - 200 employees
Learn more about McChrystal Groupexternal

$125K - $190K/yr

Full-time

Re-posted 25 days ago

Key responsibilities

  • Conduct research and analysis related to labor markets, compensation, talent availability, workforce composition, organizational structures, skills, and recruiting dynamics.

  • Acquire data from public, commercial, and proprietary sources, develop custom web scraping, extraction, and enrichment workflows, and evaluate data quality.

  • Apply machine learning, natural language processing, statistical methods, and AI techniques to solve talent intelligence problems and develop analytical approaches.

Job description

Position Overview: 

Our consultants work side by side with client organizations to help them make smarter decisions about their people. The Talent Intelligence Research Engineer is the analytical engine behind that work. 

In this role, you will be embedded on client-facing consulting teams, working directly with clients to answer complex questions about their workforce and talent landscape. The data you work with spans publicly available talent and talent-adjacent data, as well as clients’ own workforce data. 

The questions you'll tackle might look like: How much should we be paying for this role in this market? Where does the talent we need actually exist, and can we compete for it? How does our workforce compare to our competitors? What skills does our organization have today, and what are we missing? 

To answer those questions, you'll pull from a wide toolkit, writing code, scraping and acquiring data from public sources, applying natural language processing, machine learning, and AI techniques, and designing custom analytical approaches when no off-the-shelf solution exists. Every engagement is different, and the problems are genuinely novel. 

This is not a role that maintains systems or runs recurring reports. It is investigative and project-based by nature. You'll move from engagement to engagement, working alongside consultants and client business leaders to develop proprietary methodologies, build analytical capabilities that don't exist anywhere else, and deliver the data assets and insights that help clients make better decisions about their talent, workforce, organization, and leadership. 

Workforce & Talent Intelligence

  • Conduct research and analysis related to labor markets, compensation, talent availability, workforce composition, organizational structures, skills, and recruiting dynamics. 

  • Develop methodologies to estimate or infer workforce attributes that are not directly observable. 

  • Analyze talent pools, labor supply, competitive hiring environments, and organizational capabilities. 

  • Produce actionable talent intelligence for client engagements. 

  • Communicate findings, assumptions, confidence levels, and limitations to both technical and non-technical audiences. 

Research Engineering & Data Acquisition

  • Acquire data from public, commercial, and proprietary sources. 

  • Develop custom web scraping, extraction, and enrichment workflows to support research initiatives. 

  • Build one-off software tools and analytical applications required to answer specific business questions. 

  • Evaluate data quality, completeness, and reliability across multiple sources. 

  • Rapidly learn and apply new technologies, techniques, and datasets as project requirements evolve. 

Machine Learning, AI & Advanced Analytics

  • Apply machine learning, natural language processing, statistical methods, and generative AI techniques to solve talent intelligence problems. 

  • Develop similarity, matching, classification, clustering, ranking, and inference approaches when appropriate. 

  • Leverage large language models and modern AI tooling to accelerate research and insight generation. 

  • Design experiments and validation approaches to assess analytical accuracy and reliability. 

  • Translate analytical outputs into practical business recommendations. 

Consulting & Collaboration

  • Partner with consultants, researchers, and client-facing stakeholders to understand business challenges. 

  • Contribute to the development of proprietary talent intelligence methodologies and intellectual property. 

  • Support client engagements through research, analytical problem solving, and technical expertise. 

  • Present research findings and recommendations to clients and internal stakeholders. 

  • Share tools, approaches, and best practices across the organization. 

Qualifications:

Required Qualifications 

  • Bachelor's degree in Computer Science, Data Science, Statistics, Economics, Mathematics, Engineering, Social Sciences, or a related quantitative field. 

  • 4-6 years of relevant experience 

  • Experience conducting independent analytical or research-oriented projects. 

  • Strong programming skills, particularly in Python. 

  • Strong analytical reasoning and problem-solving abilities. 

  • Ability to work effectively in ambiguous environments with limited precedent or direction. 

  • Excellent written and verbal communication skills. 

  • Experience with labor market, workforce, recruiting, compensation, or organizational data. 

  • Experience working with large structured and unstructured datasets. 

  • Must be able to obtain and maintain a U.S. Government security clearance. 

Preferred Qualifications 

  • Experience with web scraping, data acquisition, and information extraction. 

  • Experience with machine learning, NLP, or AI-assisted analytics. 

  • Exposure to consulting, market intelligence, economic research, competitive intelligence, or workforce analytics environments. 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.