Jobs and Careers
MA
Junior AI/ML Engineer
ManTechUnited Statesfull_timeVerifiedPosted 3 Jun 2026
About the role
General information
Requisition #
R68323
Locations
USA-VA-Arlington
Posting Date
06/02/2026
Security Clearance Required
Secret
Remote Type
Onsite
Time Type
Full time
Description & Requirements
Elevate your career with MANTECH International Corporation! Join a dynamic team dedicated to national security through cutting-edge technology. Since 1968, MANTECH has led in delivering advanced solutions to government intelligence, the Department of Defense, and Federal Civilian sectors. Dive into innovation in Digital Transformation, Cybersecurity, IT, Data Analytics and Software Development. Your journey to impactful work and rapid growth starts now—be extraordinary at MANTECH!
***This is for a future opportunity***
***This is for a future opportunity***
MANTECH seeks a motivated, career and customer-oriented Junior AI/ML Engineer to join our team. On site at the Pentagon.
Responsibilities include, but are not limited to:
- Design, build, and maintain AI/ML lifecycle core services and products
- Create utilities and ensure seamless function of orchestration capabilities to support the AI/ML environment
- Develop and implement infrastructure for training, validating, and deploying machine learning models
- Create reusable components and libraries to accelerate AI/ML development and use of Generative AI capabilities
- Build model serving platforms for efficient inference
- Implement automated machine learning pipelines and MLOps practices for continuous integration and deployment (CI/CD) of models
- Implement version control for models and datasets, and develop robust testing frameworks for AI/ML components
Minimum Qualifications:
- Bachelor's degree in Computer Science, Statistics, Engineering or other related discipline
- 2+ years of experience
- 3+ years of software engineering experience with deep proficiency in Python
- Proven experience operationalizing Machine Learning models in production environments
- Familiarity with MLOps frameworks such as AWS SageMake, MLflow, Kubeflow, or Airflow.
- Expertise in scalable model serving platforms such as TensorFlow Serving, TorchServe, or ONNX runtime.
- Advanced knowledge of cloud platforms (e.g., AWS, Azure, or GCP) and DevOps practices including Terraform or Helm.
Preferred Qualifications:
- Hands-on experience with Kubernetes and deploying containerized ML services
- Experience working with feature stores
- Experience utilizing Databricks or similar cloud-native ML tooling
- Experience working with feature stores and distributed data frameworks (e.g., Spark).
- Proficiency in model interpretation tools like SHAP or LIME.
- Foundational und
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