AI/ML Engineer

🕒 July 30

🏛️ District of Columbia, Washington – Remote

🏛️ District of Columbia – Remote ☕ Washington – Remote

💵 $108.4k - $203.4k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Accenture Federal Services

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2017

💼 Consulting

🎖️ Defense

📦 Logistics

Consulting • Defense • Logistics

Accenture Federal Services is a division of Accenture that focuses on delivering technology and consulting services to the U. S. federal government. With capabilities in cloud, cybersecurity, data and artificial intelligence, digital engineering, and emerging technologies, Accenture Federal Services supports federal agencies in achieving mission-critical outcomes through innovation and technological advancement. The company emphasizes building secure, scalable solutions, enhancing decision-making with data-driven insights, and transforming digital infrastructures to meet complex governmental needs. By leveraging advanced R&D and human-centered design, they aim to improve the performance and resilience of government operations.

📋 Description

• Develop MLOps frameworks and workflows for a variety of domains and applications • Build, train, deploy, and maintain machine learning models in production environments. • Design, develop, and maintain end-to-end ML pipelines, including data ingestion, feature engineering, training, validation, deployment, and monitoring. • Implement MLOps frameworks and best practices, including CI/CD pipelines, model versioning, model registries, feature stores, and automated retraining workflows. Deploy, monitor, and optimize machine learning solutions using cloud platforms and containerized technologies such as Docker, Kubernetes, SageMaker, Vertex AI, or Azure ML. And the last one. • Collaborate across engineering and data teams to integrate scalable ML solutions into mission-critical applications while monitoring performance and addressing model drift.

🎯 Requirements

• Hands-on experience building, training, deploying, and maintaining machine learning models in production environments. • Strong proficiency in Python and experience with one or more machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, XGBoost or Hugging Face. • Experience developing and maintaining end-to-end machine learning pipelines, including data ingestion, feature engineering, model training, validation, deployment, and monitoring. Experience with MLOps practices and tools, including model versioning, CI/CD pipelines, model registries, feature stores, model monitoring, and automated retraining workflows. Experience deploying machine learning models using cloud native or containerized technologies such as Docker, Kubernetes, Amazon SageMaker, Google Vertex, AI or Azure Machine Learning. • Experience monitoring production machine learning systems, troubleshooting model performance issues, and addressing model drift. • Must be a U.S. Citizen (No Dual citizenship).

🏖️ Benefits

• Accenture Federal Services offers a wide variety of benefits.