Apply on Employer Site

Leidos · 20 hours ago

Principal AI/ML Engineer (SWE-4)

Fort Meade, MD

Full-time

Onsite

Senior Level, Lead/Staff

$154K/yr - $278K/yr

11+ years exp

Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. The Principal AI/ML Engineer will support the Corporate Discovery Services mission by bridging data science and software engineering to deliver robust, scalable prototypes and deploy solutions.

ComputerGovernmentInformation ServicesInformation TechnologyNational SecuritySoftware

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

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

Qualification

Machine Learning Operations (MLOps)PythonTensorFlowPyTorchAWS SageMakerDockerKubernetesSoft Skills

Required

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

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)

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