Senior Machine Learning Engineer

Leidos; United States; On-site; USD 140,000 - 200,000; Full time

Job summary

Leidos' Security Enterprise Solutions (SES) is seeking a Senior Machine Learning Engineer to advance MLOps for object-detection systems supporting border security products. You will lead training, evaluation, and deployment of models, partnering with data scientists, software engineers, and domain experts.

The role emphasizes scalable pipelines, reproducible experiments, and ongoing monitoring to ensure robust performance in production environments, with travel up to 25% as needed.

Qualifications

• Requires MS or PhD in Data Science or related field with 10+ years industry experience.
• Experience managing full ML lifecycle from data prep to deployment and monitoring.
• Experience with MLflow, DVC, or LakeFs for experiments and data versioning.
• Experience deploying ML models in production with Docker or Kubernetes.
• Familiarity with cloud platforms and data warehouses.
• Strong cross-functional collaboration and communication.
• Willingness to travel up to 25%.
• Ability to obtain Public Trust access.

Responsibilities

• Develop, train, and evaluate ML models using modern MLOps practices and frameworks.
• Design and maintain reproducible training pipelines that support scalable 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.

Skills

ML lifecycle

Docker/Kubernetes deployment

MLflow / DVC tracking

Cross-functional collaboration

Excellent communication

Education

MS or PhD in Data Science/Engineering

Tools

Kubeflow

Airflow

Job description

Description

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.

Key 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

Required Qualifications

Data Science & Technical Foundation

• 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.

Desired / Nice‑to‑Have Qualifications

• 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

Commitment to Non‑Discrimination

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.