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About This Role
JOB ID: 729769BR
Date posted: May. 28, 2026
Description:
Lockheed Martin Missiles \& Fire Control (MFC) is seeking a Senior AI/ML Engineer to join The Forge, our internal data and AI consultancy. You will partner with high visibility Missile and Fire Control programs to translate raw data into AI driven solutions that cut costs, accelerate production, and sustain our competitive edge. This is a hands on, customer facing role where your expertise will shape the future of Aerospace and Defense engineering.
The Work:
As Senior AI/ML Engineer for The Forge you will take on a leadership role, owning the technical execution of the program customer project. You will leverage advanced analytics, statistical modeling, and machine learning to drive data\-driven decision making across MFC engineering and production. You will apply advanced statistical techniques, machine learning algorithms, and data visualization methods to identify trends, patterns, and correlations in data from engineering development and production sources. You will develop, implement, and advocate for AI\-powered solutions.
Some of the core responsibilities will be:
Design, develop, and deploy end to end AI/ML pipelines that support engineering design, manufacturing, and business operations challenges (e.g., test point reduction, automated calibration, AI enhanced document search, computer vision inspection).
Build and implement edge deployed AI/ML solutions for classified, air gapped environments.
Lead cross functional solution teams, Engineering Design \& Development, Production, and Business Operations, using a standard consulting style project framework.
Partner directly with program customers to understand pain points, define value driven outcomes, and deliver measurable results (cost, labor, yield, schedule).
Own the full DevOps lifecycle: CI/CD, containerization, model monitoring, and governance for secure, high assurance AI in defense systems.
Who We Are:
The Forge is Lockheed Martin Missiles \& Fire Control internal data and AI consultancy, created to meet the accelerating pressure of firm fixed price contracts and rapid program ramps. Operating like an independent consulting firm inside Lockheed Martin, we deliver AI enabled insights that drive critical cost and schedule reduction initiatives. Our customer centric, value first mindset makes us a trusted partner across engineering, production, and business ops, turning complex data into decisive, cost saving actions.
Who You Are:
You are a technically proficient leader with years of hands\-on experience building and scaling AI/ML solutions, ranging from supervised/unsupervised machine learning, deep learning models, computer vision systems or large language models. Your background includes solid engineering design work in aerospace or defense, giving you an intimate understanding of design processes, tools, and challenges. You approach every engagement with a consulting mindset, scoping, delivering, and rigorously measuring value for internal customers, while communicating complex concepts clearly to senior stakeholders. A proactive lifelong learner, you stay ahead of the latest AI tools and trends and actively share that knowledge across the team. You thrive autonomously, taking full ownership of end\-to\-end projects, and you excel in customer facing roles where you build trust, drive results, and champion continuous improvement.
This position is onsite in Orlando, Florida. We offer flexible work schedules to comprehensive benefits investing in your future and security,
Further Information About This Opportunity:
This position is in Orlando. Discover more about our Orlando, Florida location.
MUST BE A U.S. CITIZEN – This position is located at a facility that requires special access. The selected candidate must be able to obtain a secret clearance. A company‑sponsored interim secret clearance is required to start.
Basic Qualifications:
- Master's or Ph.D. degree in Computer Science, Computer Engineering, Data Science, Applied Mathematics, Engineering, Physics or a related field
- Must be a US Citizen and have the ability to obtain a Department of Defense Secret Clearance, Interim required to start.
- Experience in AI/ML research and development, with a strong background in machine learning, deep learning, and generative AI such as LLMs
- Proficiency with python and agentic IDEs
- Experience with AI/ML frameworks and libraries, including TensorFlow, PyTorch, and MCPs
- Must have the ability to lay out technical roadmaps and communicate those plans and solutions to both highly technical and non\-technical stakeholders
Desired Skills:
- Strong interpersonal skills and an ability to build effective working relationships
- Strong problem\-solving mindset with the ability to create solutions to difficult problems often requiring integration of conflicting and, at times, ambiguous or incomplete data on a rapid schedule
- Excellent technical and executive communication skills
- Experience with AI/ML ethics, fairness, and transparency
- Strong understanding of statistical modeling, machine learning techniques, agentic systems and LLMs
- Experience in full AI System solutioning including but not limited to, MLOps, retrieval systems, security, frontend UX/UI design, reliability, evaluation and verification
Security Clearance Statement:
This position requires a government security clearance, you must be a US Citizen for consideration.
Clearance Level:
Secret
Other Important Information You Should Know
Expression of Interest:
By applying to this job, you are expressing interest in this position and could be considered for other career opportunities where similar skills and requirements have been identified as a match. Should this match be identified you may be contacted for this and future openings.
Ability to Work Remotely:
Onsite Full\-time: The work associated with this position will be performed onsite at a designated Lockheed Martin facility.
Work Schedules:
Lockheed Martin supports a variety of alternate work schedules that provide additional flexibility to our employees. Schedules range from standard 40 hours over a five day work week while others may be condensed. These condensed schedules provide employees with additional time away from the office and are in addition to our Paid Time off benefits.
Schedule for this Position:
4x10 hour day, 3 days off per week
Lockheed Martin is an equal opportunity employer. Qualified candidates will be considered without regard to legally protected characteristics.
The application window will close in 90 days; applicants are encouraged to apply within 5 \- 30 days of the requisition posting date in order to receive optimal consideration.
Join us at Lockheed Martin, where your mission is ours. Our customers tackle the hardest missions. Those that demand extraordinary amounts of courage, resilience and precision. They’re dangerous. Critical. Sometimes they even provide an opportunity to change the world and save lives. Those are the missions we care about.
As a leading technology innovation company, Lockheed Martin’s vast team works with partners around the world to bring proven performance to our customers’ toughest challenges. Lockheed Martin has employees based in many states throughout the U.S., and Internationally, with business locations in many nations and territories.
Experience Level:
Experienced Professional
Business Unit:
MISSILES AND FIRE CONTROL
Relocation Available:
Possible
Career Area:
Software Engineering
Type:
Full\-Time
Shift:
First
At Lockheed Martin, we apply our passion for purposeful innovation to keep people safe and solve the world's most complex challenges.
Pioneering Defense Technology: From aerospace to outer space to cyber space, you can innovate mission solutions alongside the best minds in the business.
United By Culture: Excellence, integrity, and collaboration define us. We accelerate change and embrace one another’s perspectives to win for our customers.
Real Impact, Real Growth: Grow your career and skills for life. Our wide array of opportunities and technology\-driven learning programs enable your development and agility.
Your Health, Your Wealth, Your Life: Competitive pay, comprehensive benefits and flexible schedules designed so you thrive — at work and beyond.
Empowered to Be Your Best: Use your strengths to make a difference in the lives of one another, our customers, our communities, and our planet.
Here, the possibilities are endless because we offer:
Flexible Schedules, dependent on role
Levels: Student, Entry, Mid, Senior, Management
Locations: Nationwide \& OCONUS Positions
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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% 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 $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Lockheed Martin AI Hiring
Lockheed Martin has 11 open AI roles right now. They're hiring across AI Software Engineer, Data Engineer, AI/ML Engineer. Positions span Manassas, VA, US, Fort Worth, TX, US, Bethesda, MD, US. Compensation range: $170K - $311K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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