Remote MLOps Engineer: Cloud AI Platform

ICF International; United States; Remote; USD 99,000 - 168,000; Full time

Job summary

ICF is seeking an ML Ops Engineer to design and maintain production-grade ML pipelines, model registries, deployment frameworks, and monitoring solutions in a cloud-based environment. You will collaborate with data scientists, data engineers, cloud architects, and Trustworthy AI stakeholders across federal programs.

This role is remote with a strong preference for candidates in the Washington DC Metro Area; occasional onsite meetings at the client site in Washington, DC are expected. U.S.

Qualifications

• U.S. Citizenship is required due to federal contract requirements.
• Candidate must reside in the U.S. and perform all work in the U.S.
• 6+ years of experience designing and supporting production ML solutions in cloud environments.

Responsibilities

• Design, build, and maintain production-grade MLOps pipelines for model training, evaluation, validation, registration, deployment, monitoring, retraining, rollback, and retirement.
• Develop reusable MLOps and LLMOps patterns using Azure Databricks, Databricks ML, MLflow, Unity Catalog, Azure Machine Learning, Python, and approved Azure AI services.
• Implement experiment tracking, model versioning, model registries, lineage, quality metrics, model cards, and approval workflows using MLflow and Unity Catalog to ensure models are discoverable, reusable, and auditable.
• Build automated CI/CD pipelines using GitHub Actions, Azure DevOps, Databricks Asset Bundles, and Terraform to promote models, code, configurations, and supporting infrastructure consistently across development, test, and production environments.
• Deploy and maintain scalable model-serving infrastructure for batch, streaming, real-time, and API-based inference workloads using Databricks Model Serving, Azure Machine Learning, Databricks compute, serverless capabilities, and GPU-enabled configurations.
• Establish automated testing and evaluation gates for model performance, data quality, fairness, safety, explainability, robustness, privacy, and release readiness.

Skills

Python

MLOps

Cloud architecture

CI/CD

Monitoring

Education

Bachelor's degree in Computer Science or related field

High school diploma with 4+ years relevant experience

Tools

GitHub Actions

Azure Databricks

MLflow

Terraform

Azure Machine Learning

Job description

ICF is seeking an ML Ops Engineer to design and maintain production-grade ML pipelines, model registries, deployment frameworks, and monitoring solutions in a cloud-based environment. You will collaborate with data scientists, data engineers, cloud architects, and Trustworthy AI stakeholders across federal programs.

This role is remote with a strong preference for candidates in the Washington DC Metro Area; occasional onsite meetings at the client site in Washington, DC are expected. U.S.