MLOps Platform Engineer | Reproducible AI in Production

Peregrine Advisors LLC; Washington (District of Columbia); On-site; USD 140,000 - 200,000; Full time

Job summary

OPEN Data Jobs in the federal sector seeks Machine Learning Engineers to build reproducible, scalable, and supportable ML platforms. You will take models from training to production with versioned data, code, and artifacts.

You will automate training and validation, manage feature stores and model registries, monitor performance and cost, and collaborate with data scientists, application engineers, and security teams to keep the system reliable.

Qualifications

• Proficiency in building scalable ML systems and pipelines.
• Experience with training, evaluation, and feature engineering.
• Familiarity with MLOps principles and deployment tooling.

Responsibilities

• Automate training/validation pipelines with versioned data and artifacts.
• Build model-serving systems and APIs with reliable latency and scalability.
• Maintain feature stores, registries, lineage, and release controls.
• Monitor data quality, drift, performance, and cost, with alerting.

Skills

Programming & software engineering

Model development

MLOps

Monitoring & observability

Cost optimization

Education

Bachelor's degree in CS or related field

Tools

Containers

Cloud compute

Artifact management

CI/CD

Deployment tooling

Job description

OPEN Data Jobs in the federal sector seeks Machine Learning Engineers to build reproducible, scalable, and supportable ML platforms. You will take models from training to production with versioned data, code, and artifacts.

You will automate training and validation, manage feature stores and model registries, monitor performance and cost, and collaborate with data scientists, application engineers, and security teams to keep the system reliable.