Principal AI/ML Engineer (SWE-4)

Leidos has a new and exciting opportunity for a Principal AI/ML Engineer in our National Security Sector's (NSS) Cyber & Analytics Business Area (CABA). Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos, we offer competitive benefits, including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more. Join us and make a difference in National Security!

Job Summary:

Our LOE program provides our customer's Operations organization with the best possible solutions for their mission needs. We achieve this through rapid prototyping, new development, and advanced technology research. From leading-edge visualizations to analytic development, we're always pushing the boundaries to find new and better data sources and tradecraft to answer intelligence questions. With a focus on collaboration and a fast-paced environment, our prototype development program is the ideal place to grow your skills and make a real impact. Click here to learn more about how this program "Delivers Mission Success!"

Seeking a motivated AI/ML Engineer to support the exciting Corporate Discovery Services mission. The AI/ML Engineer will act as the critical bridge between data science and software engineering mission capturing requirements from stakeholders to deliver robust, scalable, and functional innovative prototypes and deploy solutions.

Job Responsibilities/Qualifications:

• Mission Focus: Use Machine Learning Operations (MLOps) set of practices to automate and standardize the lifecycle of machine learning models, from development and training to deployment and monitoring, borrowing principles from DevOps to ensure reliable, efficient, and scalable ML systems in production. Create Machine Learning, Generative AI Large Language Models (LLM), Retrieval Augmented Generation (RAG), and Agentic AI AI/ML pipelines.
• Technical Proficiency: Proficiency in Python with TensorFlow, PyTorch, Scikit-learn, Keras, PySpark, vLLM, and NVIDIA CUDA (Compute Unified Device Architecture) libraries. Strong grasp of version control (GitLab), Continuous Integration/Continuous Deployment (GitLab CI/CD), and containerization (Docker, Kubernetes).
• Qualifications: Bachelor's degree in computer science or related technical field plus a minimum of eleven (11) to fifteen (15) years of relevant experience.
• Security Clearance Requirement: Candidates must possess an active TS/SCI with Polygraph to be considered for this role.
• Desirable Skills: MLOps, AWS SageMaker, AWS Bedrock, Gambit, Hub, Jira, Confluence, Docker Hub.
  
  

At Leidos, the opportunities are boundless. We challenge our staff with interesting assignments that allow them to thrive professionally and personally. For us, helping you grow your career is good business. We look forward to learning more about you - apply today!

Careers.leidos.com

conmd

Come break things (in a good way). Then build them smarter.

We're the tech company everyone calls when things get weird. We don't wear capes (they're a safety hazard), but we do solve high-stakes problems with code, caffeine, and a healthy disregard for "how it's always been done."

Original Posting:

December 19, 2025

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $154,050.00 - $278,475.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.