ML Ops Engineer / Lead

ML Ops   Engineer / lead

Location:- Reston, VA

Seeking a Full Stack Machine Learning Engineer to support the ML Ops workstream within their broader model transformation program. This is a hands-on engineering role with strong emphasis on AWS, SageMaker, and end to end ML model operationalization.

Key Responsibilities

•       Build and operationalize ML models using AWS SageMaker.

•       Work closely with:

oxxxxxxxxxxxxxxxData Science team on model development and operationalization.

oxxxxxxxxxxxxxxxTechnology team to validate platform integration and functionality.

•       Act in a product owner like capacity for the ML Ops platform—ensuring alignment with model development needs.

•       Validate end to end ML Ops integrations (SageMaker, GitLab, Terraform, etc.).

•       Help close gaps between data science and technology teams during initial platform implementation.

•       Support model retraining, deployment strategies, and iterative model lifecycle processes.

Required Technical Skills

Suppliers should ensure candidates meet the following must have requirements:

Core Technical Competencies

•       Strong AWS experience, especially SageMaker (processing, MLflow model registry, etc.).

•       ML Ops expertise, including understanding of DevOps principles.

•       Experience integrating ML systems with GitLab, Terraform, and similar tools.

•       Python proficiency is mandatory (primary language for ML at Fannie Mae).

oxxxxxxxxxxxxxxxR is supported but secondary.

•       Strong data engineering skills:

oxxxxxxxxxxxxxxxFeature engineering

oxxxxxxxxxxxxxxxData sourcing

oxxxxxxxxxxxxxxxWorking with large datasets

•       Solid understanding of the end to end model development lifecycle.

Preferred Profile Traits

•       Ability to lead directionally, not just follow instructions.

•       Comfortable working cross functionally across business, technology, and data science.

•       Hands on approach; not a conceptual-only role.

Work Expectations

•       Preference for candidates who can work onsite at MTC where the data science team is located.

•       Flexibility in interview location; may occur virtually via Teams.