Senior Machine Learning Engineer

Leidos•Vista, CA

4d•Onsite

About The Position

Leidos’ Security Enterprise Solutions (SES) operation is seeking a motivated and talented Senior Machine Learning Engineer to join our multidisciplinary, highly energized, and expert data science team. Leidos is a leading innovator in deploying AI solutions, and we are dedicated to pushing the boundaries of technology and data-driven insights. Join our dynamic team and be part of shaping the future and make global impact in border security. We are seeking a Senior Machine Learning Engineer to work on MLOPS that support the testing, and release of object detection algorithms for our portfolio of products that help safeguard the flow of cargo and vehicles through ports and borders worldwide. The ideal candidate is a senior level individual contributor and subject matter expert, who excels at taking requirements defined by business needs and generating MLOPS solutions.

Requirements

MS or Ph.D. in Data Science, Engineering, Applied Science or a similar discipline and a minimum of 10 years of industry experience
Ability to support the full ML lifecycle, from data preparation and training to deployment and monitoring
Experience tracking experiments, model performance, and model versioning using a platform like MLflow to ensure transparency and auditability
Experience with data versioning frameworks like DVC, MLFlow Dataset, or LakeFs
Experience deploying and managing machine learning models in production environments using Docker or Kubernetes
Familiarity with modern data stacks e.g., cloud platforms, data warehouses, MLOps concepts
Ability to evaluate technical approaches and guide technical decision-making
Strong track record of delivery ownership and cross-functional collaboration
Ability to multitask across projects
Excellent communication skills, both written and verbal
Some travel is required in support of projects (< 25%)
Ability to obtain and maintain Public Trust access.

Nice To Haves

Experience using Kubeflow or Airflow
Familiarity with CNN-based machine learning architectures, e.g., ResNet, Yolo, U-Net
Experience working with images from medical, security, or NDT devices
Experience defining data science standards and best practices
Experience in training machine learning models with synthetic data, that can achieve high detection during real-time inference
Experience working on Customs and Border Patrol contracts

Responsibilities

Develop, train, and evaluate machine learning models using modern MLOps practices and frameworks
Design and maintain reproducible training pipelines that support scalable and repeatable experimentation
Collaborate with cross-functional teams to integrate models into operational systems and workflows
Optimize model performance and reliability through continuous monitoring, testing, and iteration