Leidos is seeking a Senior Machine Learning (MLOps) Engineer to develop and deploy Trusted Mission AI solutions, focusing on AI agents that automate and optimize labor-intensive workflows, ensuring accuracy, security, and reliability in operational environments.
Requirements
- Hands-on experience on building, automating, and managing AI/ML pipelines, and MLOps capabilities (Kubeflow, MLflow, etc.)
- Advanced Python programming skills
- Experience with AI/ML tools, such as common python packages (e.g., scikit-learn, TensorFlow, PyTorch) and Jupyter notebooks
- Experience with MLOps tools and frameworks, such as Kubeflow, MLflow, DVC, TensorBoard
- Experience with Software Development tools, including Git, containerization technologies (e.g., Docker), CI/CD frameworks
- Experience with automated deployment pipelines for Agentic AI Models
- Competence in troubleshooting and mitigating issues with prototyped and deployed AI
Responsibilities
- Design, implement, and maintain tools that enable agent deployments using MLOps best practices in scalable cloud infrastructure
- Develop and document processes that enable secure automated development and deployment of AI agents
- Design, build, train, and evaluate Machine Learning models
- Build repeatable Machine Learning pipelines for model training, evaluation, deployment, and monitoring
- Perform R&D to enable AI Observability and performance metrics
- Design, implement, and manage cloud resources for MLOps infrastructure
- Work in a team of AI/ML researchers and engineers using Agile development processes
Other
- Collaborate with multidisciplinary teams
- Highly motivated and collaborative, working well independently and within a team
- Ability and willingness to obtain a Top Secret security clearance
- Ability to work in fast-paced, Agile development teams
- Motivated to ask “what’s next?”
