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# A/AI Machine Learning Engineering - E2

- **Company:** Lockheed Martin
- **Location:** Fort Worth, TX, United States
- **Salary:** $81,100.0 - $150,500.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Computer Programming, Software Debugging, Linux, Distributed Systems, Human-Computer Interaction, Python (Programming Language), Machine Learning, Software Engineering, Software Systems, Systems Integration, Delivery Pipeline, Software Troubleshooting, Kubernetes, Information Technology, Machine Learning Operations, Data Pipelines, Docker
- **Published:** September 16, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9166291/aai-machine-learning-engineering-e2

## About the Role

Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or related field

 - 1+ years of experience in software engineering or systems integration

 - Strong programming skills in one or more of the following: Python, C++, Java

 - Experience applying and integrating AI/ML concepts and frameworks (e.g., model integration, inference pipelines, or data processing workflows)

 - Experience working in Linux-based development environments

Desired Skills

Ability to debug and resolve complex, cross-domain technical issues

 - Experience working with software integration, APIs, and distributed systems

 - Experience integrating machine learning models into production or test environments

 - Familiarity with simulation environments or hardware/software lab integration

 - Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes)

 - Knowledge of data pipelines, MLOps practices, or model lifecycle management

 - Experience with real-time or embedded systems

## Description

You will work alongside software developers, system engineers, and test teams to integrate, evaluate, and mature AI-enabled features prior to formal system integration, verification, and validation. The ideal candidate is a strong software engineer who is comfortable working across system boundaries and is motivated to apply AI to solve real-world engineering challenges., Integrate AI/ML capabilities into existing and emerging software systems, simulation frameworks, and lab environments

 - Collaborate with software developers to incorporate AI-driven features early in the development lifecycle

 - Develop and maintain integration pipelines across virtual and hardware-based test environments

 - Design, implement, and evaluate AI-enabled workflows for system-level capabilities

 - Troubleshoot complex integration issues spanning software, data, and system interfaces

 - Contribute to the development of tools, automation, and infrastructure that enable scalable AI integration

 - Work with cross-functional teams to define data requirements, interfaces, and performance metrics for AI-enabled development

 - Advocate and champion use of AI throughout the development lifecycle

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


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