AI Machine Learning Engineering Sr

Posted 2 Hours Ago
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9 Locations
In-Office or Remote
110K-228K Annually
Senior level
Aerospace • Security • Cybersecurity • Industrial
The Role
Develops, integrates, tests, and deploys AI, machine learning, autonomy, perception, planning, and control algorithms for mission systems. Translates requirements into production-grade machine-learning pipelines and software, integrates generative AI and LLM capabilities, troubleshoots implementations, and supports research-driven innovation. Collaborates with stakeholders, documents interfaces, develops human-machine interaction scenarios, and advances enterprise AI adoption.
Summary Generated by Built In
Standard Job Description

The AI Research & Enterprise Solutions (AIRES) team within Lockheed Martin’s Data & AI Enablement organization(D&Ae) creates tailored, production‑grade AI solutions that enable success across the corporation. In this role you will partner with internal stakeholders to translate complex requirements into end‑to‑end machine‑learning pipelines, integrate large‑language‑model capabilities, and drive research‑focused innovations that accelerate AI adoption enterprise‑wide. Your expertise in Python, the data‑science lifecycle, deep‑learning fundamentals, and emerging generative‑AI technologies will empower you to deliver high‑impact, mission‑critical solutions that generate measurable value for Lockheed Martin.


Responsible for developing, integrating, and deploying autonomy and artificial intelligence algorithms for mission systems, supporting the technology development life cycle from requirements generation through development, integration, and testing, as well as research in some organizations.Develops, integrates, and implements algorithms to enable perception, motion/mission planning, controls, etc. functionality in LM products and platforms; Translates requirements and applies requirements to development code, integrating autonomy, AI or machine learning algorithms to LM products and platforms; Determines software methods to best acquire and execute knowledge; Implements algorithms into software to train systems to recognize patterns and perform specific functions; Responsible for various phases of developing and maintaining autonomy software from requirements generation, software design and development to integration, testing, troubleshooting and debugging, and implementation; Review test outcomes, conducts troubleshooting, and works to debug issues; Develops human-machine interface scenarios, breaking missions into tasks; Documents interface requirements and implements human-machine interfaces

Basic Qualifications
  • Bachelor’s degree in Computer Science, Information Technology, Engineering, AI/ML, or a related discipline.
  • Proficiency in Python – write clean, well‑documented code and explain your logic.
  • Knowledge of the data‑science lifecycle, big‑data concepts, deep‑learning fundamentals, and reinforcement‑learning ideas.
  • Basic awareness of Generative AI capabilities such as large‑language models (LLMs)
  • Demonstrated initiative and research mindset – comfortable navigating documentation, exploring new tools, and proposing ideas.
  • Strong problem‑solving and communication skills; able to work with internal customers to gather requirements and provide clear status updates.
 
Desired Skills
  • Experience with LLM frameworks or APIs (e.g., LangChain, OpenAI, Cohere).
  • Exposure to MLOps fundamentals: CI/CD pipelines, model versioning, monitoring, Docker/Kubernetes.
  • Knowledge‑graph or ontology work (SPARQL, embeddings, graph‑based feature engineering).
  • Familiarity with cloud platforms (AWS, Azure, GCP) and OpenShift.
  • Ability to quickly absorb new tools, applications, or approaches from documentation or public repositories and contribute ideas to the team.
  • Research‑oriented mindset – conducting industry/academic research, networking with peers, and surfacing innovative strategies.
  • Breadth of interest or experience with diverse data‑application domains (structured, unstructured, time‑series, sensor, etc.).
  • Experience with Git fundamentals (branching, merging, pull‑requests, basic workflow conventions).
  • Understanding of RESTful APIs and ability to integrate them into data pipelines.
  • Basic familiarity with Docker (or comparable container technology).

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): $122600.00 - $227600.00 
    • 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): $110300.00 - $204900.00 
    • Includes metropolitan areas such as Denver, CO; King of Prussia, PA; Stratford, CT; Moorestown, NJ; etc.
  • Full-time salary range (GEOZONE 3): $98100.00 - $182100.00
    • Includes metropolitan areas such as Dallas–Fort Worth, TX; Orlando, FL; Grand Prairie, TX; Marietta, GA; etc.
  • Full-time salary range (GEOZONE 4): $88300.00 - $163900.00
    • 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.

Skills Required

  • Bachelor's degree in Computer Science, Information Technology, Engineering, AI/ML, or a related discipline
  • Proficiency in Python, including writing clean, well-documented code and explaining technical logic
  • Knowledge of the data-science lifecycle, big-data concepts, deep-learning fundamentals, and reinforcement-learning ideas
  • Basic awareness of generative AI capabilities, including large language models
  • Demonstrated initiative and research mindset, including navigating documentation, exploring tools, and proposing ideas
  • Strong problem-solving and communication skills, including gathering requirements and providing status updates
  • Experience with LLM frameworks or APIs such as LangChain, OpenAI, or Cohere
  • Exposure to MLOps fundamentals, CI/CD pipelines, model versioning, monitoring, Docker, or Kubernetes
  • Knowledge-graph or ontology experience, including SPARQL, embeddings, or graph-based feature engineering
  • Familiarity with AWS, Azure, GCP, or OpenShift
  • Research-oriented mindset and experience conducting industry or academic research
  • Experience with diverse data domains, including structured, unstructured, time-series, or sensor data
  • Experience with Git branching, merging, pull requests, and workflow conventions
  • Understanding of RESTful APIs and their integration into data pipelines
  • Basic familiarity with Docker or comparable container technology

Lockheed Martin Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lockheed Martin and has not been reviewed or approved by Lockheed Martin.

  • Retirement Support — Retirement benefits are described as a standout element, with a strong 401(k) program and options like an employee stock purchase plan. Feedback suggests these features meaningfully enhance total compensation and long‑term financial security.
  • Healthcare Strength — Healthcare coverage is portrayed as comprehensive from day one, with multiple plan options, mental health resources, and virtual care. Wellness supports such as on‑site services and preventive programs are also highlighted.
  • Flexible Benefits — Work arrangements often include compressed schedules and telework, contributing to a favorable work‑life balance. Feedback suggests this flexibility is a key reason many view the overall package positively.

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The Company
HQ: Bethesda, MD
108,588 Employees
Year Founded: 1912

What We Do

Customer Focus, Innovation and Purpose are Built Into Everything We Do. Lockheed Martin. Your Mission is Ours ™. Headquartered in Bethesda, Maryland, Lockheed Martin is a global security and aerospace company principally engaged in the research, design, development, manufacture, integration and sustainment of advanced technology systems, products and services.

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