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 with minimal supervision.
• 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).