MLOps Engineer – Production ML for Federal Systems

Accenture Federal Services; United States; Remote; USD 108,000 - 203,000; Full time

Job summary

Accenture Federal Services in the United States is seeking an experienced ML Engineer to design, build, and operate ML models in production across defense, homeland security, and civilian domains. You will implement MLOps pipelines, collaborate with data and software engineers, and deploy models on cloud platforms using Docker, Kubernetes, and major ML services.

This role requires US citizenship and hands-on expertise in end-to-end ML lifecycle, with a commitment to mission-focused impact and

Qualifications

• Hands-on experience building, training, deploying, and maintaining ML models in production.
• Strong Python skills and experience with ML frameworks like PyTorch, TensorFlow, Scikit-Learn, XGBoost.
• Experience developing end-to-end ML pipelines with MLOps including CI/CD and monitoring.
• Experience deploying ML models using cloud-native or containerized tech (Docker, Kubernetes, SageMaker, Vertex AI, Azure ML).
• Experience monitoring production ML systems and addressing model drift.
• U.S. Citizenship required.

Responsibilities

• Develop MLOps frameworks and workflows for multiple domains and applications.
• Build, train, deploy, and maintain ML models in production.
• Design end-to-end ML pipelines: data ingestion, feature engineering, training, deployment, monitoring.
• Apply MLOps best practices: CI/CD, model versioning, registries, feature stores, retraining workflows.
• Collaborate with engineering and data teams to integrate ML solutions into mission-critical apps while monitoring performance.

Skills

ML in production

Python proficiency

ML frameworks

MLOps practices

US Citizenship

Education

Advanced STEM degree

Tools

Docker

Kubernetes

SageMaker

Vertex AI

Azure ML

Job description

Accenture Federal Services in the United States is seeking an experienced ML Engineer to design, build, and operate ML models in production across defense, homeland security, and civilian domains. You will implement MLOps pipelines, collaborate with data and software engineers, and deploy models on cloud platforms using Docker, Kubernetes, and major ML services.

This role requires US citizenship and hands-on expertise in end-to-end ML lifecycle, with a commitment to mission-focused impact and