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Standard Job Description
Leads those focused on research & development of technologies that enable and advance semi and fully autonomous systems for both defense and commercial customers. Serves as the algorithm expert with up-to-date knowledge on modern AI research and may be involved in the inception of ideas and drive the development cycles from research to test of prototypes for a major project or component of a major project.Leads the research and discovery of improvements to machine learning and robotic algorithms; Drives advancements in techniques used in signal processing, computer vision (CV), and control systems; Develops AI algorithms for mission systems; Applies latest research on AI algorithms and trains machine learning / deep learning models to solve a variety of problems; Investigates and applies the latest machine learning and deep learning techniques; Optimizes the performance of AI algorithms, applications, and platforms; Develops and documents algorithm and implementation requirements; Develops prototypes that will enable autonomous functionality in LM products and platforms; Interfaces with other teams involved the development lifecycle for perception, mission and motion planning, simulation and modeling, testing, etc. Proficient in AI prompting as it applies to this position and practice.
Basic Qualifications
- Bachelor’s degree in engineering, computer science, mathematics, physics, or a related technical field.
- Ten or more years of professional experience in artificial intelligence, machine learning, autonomy, robotics, or a closely related field.
- Five or more years of experience leading technical teams, research organizations, or engineering programs.
- Demonstrated experience leading AI or autonomy technology from inception through integration, evaluation, and delivery to an internal or external customer.
- Experience building customer relationships and translating mission or business needs into technical strategies and executable programs.
- Ability to critically evaluate advanced AI and autonomy concepts and communicate complex technical matters clearly to scientists, program leaders, customers, and senior executives.
- Ability to obtain and maintain a U.S. Government TS/SCI security clearance.
Desired Skills
- Master’s degree or PhD in a relevant technical discipline.
- Experience in aerospace, defense, intelligence, or national-security missions.
- Experience shaping, winning, and executing government-sponsored 6.1, 6.2, or 6.3 research and development programs.
- Demonstrated success managing a new-business pipeline, leading competitive captures and proposals.
- Experience managing an R&D portfolio and associated technolgoy roadmaps.
- Technical knowledge across several relevant areas, including automated command and control, battle damage assessment, autonomous planning and control, multi-agent systems, human-machine teaming, computer vision, reinforcement learning, edge AI, generative AI, and AI assurance.
- Experience establishing productive research partnerships with government laboratories, universities, or small businesses.
- Record of technical accomplishment demonstrated through delivered systems, successful programs, patents, publications, invited presentations, or recognized leadership in the AI community.
Pay Information
GeoZone Definition: GeoZones are geographic groupings created by Lockheed Martin to align compensation ranges with regional labor markets and cost-of-labor differences across the United States. Locations are assigned a Geo Zone based on the primary work location of the role.
- Full-time salary range (GEOZONE 1): $228100.00 - $423700.00 + Includes metropolitan areas such as Sunnyvale CA; Pal Alto, CA; New York City metropolitan area; Newark, New Jersey; etc.
- Full-time salary range (GEOZONE 2): $205300.00 - $381300.00 + Includes metropolitan areas such as Denver, CO; King of Prussia, PA; Stratford, CT; Moorestown, NJ; etc.
- Full-time salary range (GEOZONE 3): $182500.00 - $338900.00 + Includes metropolitan areas such as Dallas–Fort Worth, TX; Orlando, FL; Grand Prairie, TX; Marietta, GA; etc.
- Full-time salary range (GEOZONE 4): $164200.00 - $305000.00 + Includes metropolitan areas such as Camden, AR; Lexington, KY; Lufkin, TX; etc.
At Lockheed Martin, we know mission success starts with taking care of our people. Our Total Rewards program is designed to attract top talent, support your well-being, and help you grow—both professionally and personally.
The salary range for this position is as listed on the requisition. Please note that the salary information listed is a general guideline only.
Lockheed Martin considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/ training, key skills as well as market(work location) and business considerations when extending an offer.
Benefits offered: Medical, Dental, Vision, Flexible work arrangements and schedules (e.g., 4x10), 401(k) match, Paid time off, Holidays, Parental Leave, EAP, Flexible Spending Accounts, Education Assistance, Life Insurance, Short-Term Disability, and Long-Term Disability.
- Annual short-term and/or long-term incentive compensation programs may be offered depending on the position. Payments under these annual programs are not guaranteed and can vary from year to year and are tied to a range of performance metrics.
- For (Washington state applicants only) Non-represented full-time employees: accrue at least 10 hours per month of Paid Time Off (PTO) to be used for incidental absences and other reasons; receive at least 90 hours for holidays. Represented full time employees accrue 6.67 hours of Vacation per month; accrue up to 52 hours of sick leave annually; receive at least 96 hours for holidays. PTO, Vacation, sick leave, and holiday hours are prorated based on start date during the calendar year.
Salary Context
This $164K-$423K range is above the 75th percentile for Research Engineer roles in our dataset (median: $192K across 50 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 9,653 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Lockheed Martin, 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 ($293K) sits 17% above the category median. Disclosed range: $164K to $423K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. 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: $272,275; VP: $235,000.
Lockheed Martin AI Hiring
Lockheed Martin has 9 open AI roles right now. They're hiring across AI/ML Engineer, Research Engineer. Positions span Manassas, VA, US, Remote, US, Mount Laurel, NJ. Compensation range: $188K - $423K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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