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About This Role
JOB ID: 732050BR
Date posted: Jun. 15, 2026
Description:
Data \& AI Enablement is seeking a Senior AI Machine Learning Engineer to join the Enterprise Interoperability Framework team. This team designs, develops, and supports software solutions that enable interoperability between disparate enterprise systems, data platforms, development tools, and AI\-enabled workflows.
The candidate will work as part of an agile engineering team and will be expected to contribute across the full software development lifecycle, including requirements analysis, system design, front\-end and back\-end development, API integration, automated testing, deployment support, troubleshooting, and sustainment. The role requires close collaboration with product owners, software engineers, data engineers, AI/ML practitioners, cybersecurity teams, DevSecOps teams, and business stakeholders to deliver secure, scalable, and maintainable solutions.
Responsibilities may include:
- Designing and developing full stack software solutions using modern front\-end, back\-end, database, and API technologies.
- Building integrations between enterprise systems through REST APIs, event\-driven patterns, middleware (e.g. eQube, Quarkus, AMQ), ETL/data pipelines, and automation frameworks.
- Developing AI\-enabled capabilities that incorporate large language models, AI services, prompt engineering, model APIs, semantic search, document analysis, or intelligent workflow automation.
- Creating and maintaining APIs and services that support interoperability, data exchange, system synchronization, and workflow orchestration.
- Implementing secure software engineering practices aligned with enterprise cybersecurity, DevSecOps, and data governance requirements.
- Collaborating with cross\-functional teams to translate business needs into technical solutions and deliver capabilities in an agile environment.
- Troubleshooting complex integration issues involving data mappings, authentication, API behavior, system dependencies, performance, and reliability.
- Supporting CI/CD pipelines and deployment activities for cloud, containerized, or enterprise\-hosted applications.
- Providing technical leadership within the team, including solution design input, code reviews, mentoring, and guidance on engineering best practices.
What’s In It For You
From onsite to remote, we offer flexible work schedules to comprehensive benefits investing in your future and security,
Do you want to be part of a company culture that empowers employees to think big, lead with a growth mindset, and make the impossible a reality? We provide the resources and give you the flexibility to enable inspiration and focus \-if you have the passion and courage to dream big, work hard, and have fun doing what you love then we want to build a better tomorrow with you.
\#EBDT
Basic Qualifications:
- Experience developing software using one or more modern programming languages, such as JavaScript, TypeScript, Python, Java, C\#, or similar.
- Experience developing full stack applications, including user interface, back\-end service, API, and database components.
- Experience designing, developing, or consuming REST APIs or similar integration interfaces.
- Experience with Git\-based software configuration management tools, such as GitLab, GitHub, Bitbucket, or similar.
- Experience working in an Agile software development environment.
Desired Skills:
- Experience developing AI\-enabled applications, including integration with large language models, AI APIs, retrieval\-augmented generation, semantic search, embeddings, prompt engineering, or intelligent workflow automation.
- Experience building enterprise system integrations using REST APIs, message queues, event\-driven architectures, middleware, ETL/data pipelines, or workflow automation.
- Experience with integration or middleware technologies, such as eQube, Quarkus, AMQ, Kafka, MuleSoft, Camel, or similar.
- Experience with DevSecOps practices, including CI/CD pipelines, automated testing, static code analysis, dependency scanning, container scanning, secrets management, or infrastructure as code.
- Experience with cloud or container platforms, such as Docker, Kubernetes, OpenShift, AWS, Azure, or similar.
- Experience with enterprise software development tools, such as GitLab, Jira, Confluence, Artifactory, Jenkins, or similar.
- Experience with Jira or GitLab APIs, webhooks, workflow automation, issue synchronization, merge request workflows, or repository automation.
- Experience with relational or NoSQL databases, including schema design, query development, data modeling, or application integration.
- Experience with secure software development practices, including authentication, authorization, role\-based access control, API security, audit logging, and secure handling of sensitive data.
- Experience with test automation, including unit testing, integration testing, API testing, end\-to\-end testing, or test\-driven development.
- Experience troubleshooting distributed applications or integrations, including API behavior, data mapping, authentication, system dependencies, observability, performance, and reliability.
- Experience mentoring engineers, leading technical design discussions, performing code reviews, or establishing engineering best practices.
- Strong written and verbal communication skills, including the ability to communicate technical concepts to technical and non\-technical stakeholders.
Clearance Level:
None
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:
Full\-time Remote Telework: The employee selected for this position will work remotely full time at a location other than a Lockheed Martin designated office/job site. Employees may travel to a Lockheed Martin office for periodic meetings.
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
Pay Rate: The annual base salary range for this position in most major metropolitan areas in California, Massachusetts, and New York is $125,100 \- $216,890\. For states not referenced above, the salary range for this position will reflect the candidate’s final work location. Please note that the salary information 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 and business considerations when extending an offer.
Benefits offered: Medical, Dental, Vision, Life Insurance, Short\-Term Disability, Long\-Term Disability, 401(k) match, Flexible Spending Accounts, EAP, Education Assistance, Parental Leave, Paid time off, and Holidays.
This position is incentive plan eligible.
Pay Rate: The annual base salary range for this position in California, Massachusetts, and New York (excluding most major metropolitan areas), Colorado, Hawaii, Illinois, Maryland, Minnesota, New Jersey, Vermont, Washington or Washington DC is $108,800 \- $191,820\. For states not referenced above, the salary range for this position will reflect the candidate’s final work location. Please note that the salary information 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 and business considerations when extending an offer.
Benefits offered: Medical, Dental, Vision, Life Insurance, Short\-Term Disability, Long\-Term Disability, 401(k) match, Flexible Spending Accounts, EAP, Education Assistance, Parental Leave, Paid time off, and Holidays.
(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.
This position is incentive plan eligible.
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.
At Lockheed Martin, we use our passion for purposeful innovation to help keep people safe and solve the world's most complex challenges. Our people are some of the greatest minds in the industry and truly make Lockheed Martin a great place to work.
With our employees as our priority, we provide diverse career opportunities designed to propel, develop, and boost agility. Our flexible schedules, competitive pay, and comprehensive benefits enable our employees to live a healthy, fulfilling life at and outside of work. We place an emphasis on empowering our employees by fostering an inclusive environment built upon integrity and corporate responsibility.
If this sounds like a culture you connect with, you’re invited to apply for this role. Or, if you are unsure whether your experience aligns with the requirements of this position, we encourage you to search on Lockheed Martin Jobs, and apply for roles that align with your qualifications.
Experience Level:
Experienced Professional
Business Unit:
ENTERPRISE BUSINESS SERVICES
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
Salary Context
This $108K-$216K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 2130 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 4,133 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 $185,000 based on 13,200 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($162K) sits 12% below the category median. Disclosed range: $108K to $216K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Lockheed Martin AI Hiring
Lockheed Martin has 12 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist, Research Engineer, Data Engineer. Positions span Manassas, VA, US, Fort Worth, TX, US, Bethesda, MD, US. Compensation range: $170K - $311K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, 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 Safety roles lead at $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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