Machine Learning Engineer- TS/SCI with Polygraph
About The Position
GDIT is seeking an experienced Machine Learning Engineer to design, build, and operate mission-grade AI/ML capabilities, including production REST services, robust data pipelines, and cloud-native MLOps. The role leads the end-to-end model lifecycle, from data management and training through deployment and monitoring; integrates AI services into enterprise applications; and supports secure, reliable delivery in accredited cloud environments. The position involves architecting scalable data pipelines and lakes; enforcing data governance, encryption, versioning, lifecycle policies, tagging, and zero-trust controls; coordinating cross-domain data movement; and generating compliance evidence to support ATO and monitoring. It also builds and scales model inference APIs and microservices, manages AWS and containerized workloads, applies infrastructure-as-code and CI/CD practices, and leads model selection, training, tuning, and evaluation for mission use cases. This is an onsite position at the customer site in Tyson's, Virginia. The role requires a current TS/SCI clearance with Polygraph and U.S. citizenship. The scheduled work week is 40 hours, and travel is less than 10%.
Requirements
- 10 or more years of related experience.
- Bachelor’s degree in Computer Science, Engineering, or a related technical discipline, or an equivalent combination of education, technical certifications or training, or work experience.
- Current TS/SCI clearance with Polygraph.
- U.S. citizenship.
- Skills in artificial intelligence, machine learning, AWS Key Management Service (KMS), and REST.
- Experience with data pipelines, data lakes, data governance, encryption, and zero-trust controls.
- Experience building and deploying REST/GraphQL inference APIs and microservices.
- Experience with AWS cloud services, Docker, Kubernetes, CI/CD toolchains, and infrastructure-as-code.
- Ability to work onsite at the customer location in Tyson's, Virginia.
Responsibilities
- Architect and implement scalable data pipelines and data lakes.
- Enforce data governance, encryption using AWS KMS, versioning, lifecycle policies, tagging, and zero-trust controls across storage and processing workflows.
- Coordinate cross-domain data movement, such as AWS Data Diode or PrivateLink, and generate continuous compliance evidence to support ATO and monitoring.
- Build, expose, and scale model inference APIs (REST/GraphQL) and microservices.
- Validate endpoints and automate production deployment documentation, including VDD and release notes.
- Design and manage AWS workloads using services such as EC2, EKS, Lambda, S3, CloudWatch, and SNS/SQS.
- Manage containerized deployments using Docker and Kubernetes within CI/CD toolchains such as Jenkins and GitHub.
- Apply infrastructure-as-code using Terraform, CloudFormation, or Ansible to deliver repeatable, compliant environments with shift-left security and automated ATO evidence.
- Lead model selection, training, tuning, and evaluation across supervised, unsupervised, and reinforcement learning.
- Apply NLP, computer vision, and agentic/GenAI approaches to mission use cases.
- Lead the end-to-end model lifecycle, including data management, training, deployment, and monitoring.
- Integrate AI services into enterprise applications and ensure secure, reliable delivery in accredited cloud environments.
Benefits
- 401(k) with company match.
- Medical plan options, including plans with Health Savings Accounts.
- Dental insurance options.
- Vision plan.
- Paid education and certifications.
- Paid vacation and holidays.
- Paid time off plans including vacation, sick and personal time, holidays, and paid parental, military, bereavement, and jury duty leave.
- Short- and long-term disability benefits.
- Life insurance and other insurance offerings, including accidental death and dismemberment, personal accident, critical illness, and business travel and accident insurance.
- Internal mobility support and professional growth opportunities.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
