Principal AI/ML Engineer (SWE-4)

Leidos•Fort Meade, MD

About The Position

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.

Requirements

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).
Bachelor's degree in computer science or related technical field plus a minimum of eleven (11) to fifteen (15) years of relevant experience.
Candidates must possess an active TS/SCI with Polygraph to be considered for this role.

Nice To Haves

MLOps
AWS SageMaker
AWS Bedrock
Gambit
Hub
Jira
Confluence
Docker Hub

Responsibilities

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.