AI Community Operations Intern

Lockheed Martin•Fort Worth, MD

1d•Remote

About The Position

By bringing together people that use their passion for purposeful innovation, at Lockheed Martin we 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 development 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. At Lockheed Martin, we place an emphasis on empowering our employees by fostering innovation, integrity, and exemplifying the epitome of corporate responsibility. Your Mission is Ours. Lockheed Martin’s Enterprise Operations AI Adoption team advances AI tools, adoption strategies, and AI‑enabled solutions across the corporation. Interns work side‑by‑side with AI strategists, adoption analysts, project managers, and business leaders to scale the work of the Lockheed Martin Artificial Intelligence Center (LAIC) into repeatable, enterprise‑wide capabilities, research, transformation, and metrics that support the 21st Century Security (21CS) vision. Role Overview As an intern you will support the team in meeting key deliverables by: - Community involvement – Assist in organizing community events (hackathons, conferences, etc.), project planning, analysis, and communications; participate in AI‑developer Q&A forums. - Creative research & solution building – Build and test prototypes for data analysis and workflows; evaluate new tool features and provide performance feedback; explore generative‑AI prompts for data augmentation and assess model performance. - Content creation & tool demonstrations – Contribute to community content (presentations, documentation, instructional videos, demos). - Collaboration with engineering & business partners – Partner with peer engineering groups, business stakeholders, and customers to ensure solutions meet requirements; help translate AI concepts into production‑ready components that deliver measurable business value. - Data & database integration – Clean, label, and curate data sets; analyze patterns, discrepancies, and improvement opportunities.

Requirements

Pursuing a Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Information Sciences & Technology, Management Information Systems, Human Centered Computing/Interaction Design.
Prior coursework or project experience in computer science, data science, software engineering, or machine learning.
Strong problem solving and communication skills.
Experience with the Python programming language.
Experience using generative AI (e.g., text, code, or image generation) as a building block to accelerate projects. Familiar with AI concepts and terminology such as prompt engineering, large language models (LLMs), and retrieval augmented generation (RAG).
Demonstrated motivation to learn new technologies.

Nice To Haves

Experience with data analysis, cleaning, and curation.
Experience with editing video content and developing training scripts to depict learning scenarios.
Understanding of core ML concepts such as supervised/unsupervised learning and model‑evaluation.
Experience with DevSecOps practices and version‑control best practices (Git, CI/CD).
Hands‑on experience with generative‑AI frameworks and APIs such as OpenAI, LangChain, or similar Generative AI platforms.
Familiarity with ML libraries and frameworks (TensorFlow, PyTorch, Keras, scikit‑learn).
Basic knowledge of techniques like regression/classification, natural‑language processing, deep learning, anomaly detection, or reinforcement learning.
Understanding of AI Ethics, AI rules & responsibilities, and AI security/data privacy

Responsibilities

Community involvement – Assist in organizing community events (hackathons, conferences, etc.), project planning, analysis, and communications; participate in AI‑developer Q&A forums.
Creative research & solution building – Build and test prototypes for data analysis and workflows; evaluate new tool features and provide performance feedback; explore generative‑AI prompts for data augmentation and assess model performance.
Content creation & tool demonstrations – Contribute to community content (presentations, documentation, instructional videos, demos).
Collaboration with engineering & business partners – Partner with peer engineering groups, business stakeholders, and customers to ensure solutions meet requirements; help translate AI concepts into production‑ready components that deliver measurable business value.
Data & database integration – Clean, label, and curate data sets; analyze patterns, discrepancies, and improvement opportunities.