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About This Role
Standard Job Description
What We're Doing
At Lockheed Martin Rotary and Mission Systems we are driven by innovation and integrity. We believe that by applying the highest standards of business ethics and visionary thinking, everything is within our reach – and yours as a Lockheed Martin employee. Lockheed Martin values your skills, training and education. Come and experience your future!
The Work
The Lockheed Martin Rotary and Mission Systems (RMS) Mission Artificial Intelligence (AI) team is looking for a Manassas Tech Lead and Manager (AI / ML focus) to lead our functional and technical team who will be responsible for our AI team in Manassas and the tough technical challenges with AI, signal processing, and creating deployable solutions. The ideal candidate is passionate about a broad range of projects from research & development to prototype development, culminating in deployment of our products to customers. The successful candidate will have a strong background in areas like: software engineering, DevOps, artificial intelligence and machine learning with a desire to be a functional manager as well. Key responsibilities include:
- Technical leadership and providing technology linkage across RMS lines of business
- Partnering with the peer engineering organizations and chief engineer offices
- Personnel management of a geographically diverse team
- Critical skill hiring and retention.
- This role is based on Manassas, VA and co-located with our high performance compute cluster.
Who We Are
Lockheed Martin is a global leader in aerospace, defense, and technology solutions. Our Manassas campus is a thriving center of engineering expertise, fostering a culture that encourages creativity, excellence, and the creation of exceptional products. Our team is made up of dedicated professionals who are passionate about pushing the boundaries of what's possible. We are on the cutting edge, inserting AI into defense systems, delivered through our AI Factory in partnership with our lines of business.
Who You Are
To excel in this role, you should possess the following qualifications and attributes:
- An innovative mindset, capable of finding solutions to complex engineering challenges.
- Commitment to excellence, attention to detail, and a dedication to delivering high-quality results.
Why Join Us
Joining Lockheed Martin means becoming part of a team that's making a significant impact in the field of engineering. When you choose to work with us, you'll enjoy:
- An excellent working environment equipped with state-of-the-art tools.
- The opportunity to work alongside industry leaders and top-notch design professionals as well as Subject Matter Experts in Sonar and Acoustics.
- A chance to be a part of solving some of the world's most challenging engineering problems regarding highly complex and integrated subsystems.
- A culture that encourages creativity, excellence, and the development of remarkable products.
If you’re ready to fuel your passion and challenge the status quo, join Lockheed Martin’s RMS Artificial Intelligence team today. You are meant to make a difference.
Basic Qualifications
- Bachelor's or Master's Degree in Software Engineering, Computer Science, Machine Learning, or related STEM degree
- Experience with AI/ML: disciplines, domain programming languages (e.g. Python, C++, Java, GO), models, frameworks, and toolsets
- Experienced leader: technical teams, first or second line management, etc.
- DevOps experience including CI/CD pipelines to build, test, deploy
- Active security clearance and willing to work onsite with our team in Manassas, VA in our advanced development lab
Desired Skills
- Experience in one or more of the AI disciplines and tooling (e.g. Natural Language Processing, Anomaly Detection, Image Recognition, Machine Learning, Predictive Modeling)
- Experience with functional management of teams and demonstrated ability to provide feedback (positive and constructive) and coaching to achieve high performance
- Strong problem solving mindset: ability to develop create solutions to difficult problems often requiring integration of conflicting and, at times, ambiguous or incomplete data on a fast-paced schedule
- Demonstrated ability to effectively communicate complex design information, technical decision and issues to both highly technical and non-technical peers
- Ability to build and maintain relationships across organizations, collaborate with others, engage in constructive conflict, and manage interpersonal dynamics
- Comfortable working in a fast paced and dynamic multi-disciplinary environment
- Strong understanding of the engineering development process throughout the requirements, development, design, build, test, and integration phases of a program & familiarity with transitioning prototype software to production, including rapid software prototyping experience to create minimal viable products for evaluation of options
Pay Information
Full-Time Salary Range: $135700.00 - $251900.00
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 $135K-$251K range is above the median for AI/ML Engineer roles in our dataset (median: $176K across 1540 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Lockheed Martin, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,000 based on 11,857 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($193K) sits 9% below the category median. Disclosed range: $135K to $251K.
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 Research Engineer ($252,000). 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 AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
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).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
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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