Senior Machine Learning Engineer

This onsite role in Vista, California offers a competitive annual salary ranging from USD 107,900 to 195,050, plus a comprehensive benefits package. You will join Leidos as a Senior Machine Learning Engineer focused on MLOps driven object detection for border security, leading the end-to-end lifecycle of models from development through deployment and integration with operational systems. The position places a premium on cross-functional collaboration, reliable delivery, and impact across mission-critical systems.

What you will do

• Develop, train, and assess machine learning models using modern MLOps practices and frameworks.
• Design and maintain reproducible training pipelines that enable scalable experimentation and clear traceability.
• Collaborate with cross-functional teams to embed models into live workflows and operational systems.
• Improve model performance and dependability through continuous monitoring, testing, and iteration.

What you bring

• MS or PhD in data science, engineering, applied science, or a related field, plus at least 10 years of industry experience.
• Capability to support the full ML lifecycle, from data preparation and model training to deployment and monitoring.
• Experience tracking experiments, evaluating model performance, and managing model versions with a platform such as MLflow to ensure transparency and auditability.
• Experience with data versioning tools like DVC, MLFlow Dataset, or LakeFs.
• Experience deploying and operating ML models in production environments using Docker and Kubernetes.
• Familiarity with modern data stacks including cloud platforms, data warehouses, and MLOps concepts.
• Strong ability to evaluate technical approaches and guide decision-making.
• A proven track record of owning delivery and collaborating across functions.
• Ability to multitask across concurrent projects and priorities.
• Excellent written and verbal communication skills.
• Some travel required up to 25% to support projects.
• Ability to obtain and maintain Public Trust access.

Technologies

• MLflow
• DVC
• MLFlow Dataset
• LakeFs
• Docker
• Kubernetes
• Kubeflow
• Airflow
• ResNet
• Yolo
• U-Net

Benefits

• Competitive compensation
• Health and Wellness programs
• Income Protection
• Paid Leave
• Retirement