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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Ai/Ml Engineer - **Company:** Lockheed Martins - **Location:** Arlington, TX, United States - **Salary:** $150,800.0 - $280,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Information Systems, Continuous Delivery, Continuous Integration, Software Debugging, Human-Computer Interaction, Python (Programming Language), Machine Learning, Language Modeling, OpenShift, Systems Development Life Cycle, OpenAI, Requirements Management, Server Administration, Software Engineering, SPARQL, Systems Integration, Scripting, Google Cloud, Feature Engineering, Large Language Models, Deep Learning, Software Troubleshooting, Generative AI, Git, Containerization, Integration Tests, Kubernetes, Information Technology, Data Management, Machine Learning Operations, Restful APIs, GPT, Software Version Control, Data Pipelines, Docker - **Published:** October 2, 2026 - **Apply:** https://www.careerbuilder.com/job-details/ai-ml-engineer-stf-arlington-va--926227e6-3702-4863-aa76-0180fd16e0e5 ## About the Role * 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)., Algorithms, Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Cloud Computing, Communication Skills, Computer Science, Continuous Deployment/Delivery, Continuous Integration, Customer/Client Research, Data Management, Data Science, Debugging Skills, Deep Learning, Docker, Documentation, GCP (Good Clinical Practices), Git, Human Machine Interface (HMI), Information Technology & Information Systems, Integration Testing, Machine Learning, Microsoft Windows Azure, Modeling Languages, Ontology, Performance Metrics, Problem Solving Skills, Python Programming/Scripting Language, REST (Representational State Transfer), Requirements Management, SPARQL, Software Administration, Software Design, Software Development, Software Development Lifecycle (SDLC), Technical Support, Testing, Training/Teaching ## Description 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 ## Related Videos - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Livecoding with AI](https://www.wearedevelopers.com/videos/1201-livecoding-with-ai) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)