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# Machine Learning Engineer

- **Company:** Booz Allen Hamilton Inc.
- **Location:** United States
- **Salary:** $77,600.0 - $176,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Amazon Web Services, Systems Engineering, Microsoft Azure, C++ (Programming Language), Cloud Computing, Python (Programming Language), Machine Learning, Kubernetes, Machine Learning Operations
- **Published:** August 19, 2026
- **Apply:** https://www.dice.com/job-detail/aa3f242d-ed89-4572-b0de-124485697739

## About the Role

* Experience with operationalizing software in the cloud such as AWS, Microsoft Azure, or Google
 * Experience with Kubernetes
 * Experience with data science or machine learning
 * Knowledge of python, java, or c++ programming
 * TS/SCI clearance
 * Bachelor's degree

Nice If You Have:

 * Experience with machine learning operations pipelines
 * Ability to deploy software into a production environment
 * TS/SCI clearance with a polygraph
 * Bachelor's degree in a STEM field
 * Security+ Certification

## Description

As a programmer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using ML techniques makes you an integral part of delivering a customer-focused solution. We need your technical knowledge and desire to problem-solve to support the space industry. As a machine learning engineer on our space team, you'll train, test, deploy, and maintain models that learn from data.

In this role, you'll contribute to the direction of mission-critical solutions by applying best-fit ML algorithms and technologies. You'll grow within a talented team of machine learning engineers across the company and collaborate with data scientists, physicists, and systems engineers to deliver world-class solutions to develop agentic AI solutions. Your skills and technical experience will help your clients navigate the landscape of ML algorithms, tools, and frameworks.

Work with us to solve real-world challenges and define ML strategy for intelligence community space projects.


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