MLOps Engineer, Mid

Overview

We are looking for an experienced machine learning engineer to design and architect an MLOps platform in the Cloud that shortens the time it takes to get new capabilities from development to production, supporting mission‑critical operations across the enterprise.

• Use your development experience to streamline the entire Dev‑to‑Prod life cycle.
• Collaborate with an Agile team to build, maintain, and extend Cloud software and infrastructure that supports machine learning.
• Implement and support continuous integration and continuous deployment pipelines for development, testing, and production environments.
• Broaden your skill set in Agile development, Cloud‑based development, containerization, and serverless computing while building software that improves national security.
• Identify and build new solutions and architecture to help customers meet their toughest challenges.

• Experience with Object‑Oriented Programming (OOP), including Python.
• Experience developing containerized applications, including API design and authentication.
• Experience building software with cloud technologies, including AWS.
• Experience leveraging MLOps platforms and CI/CD workflows to manage datasets, model training, deployment, and monitoring.
• Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem.
• TS/SCI clearance with a polygraph.
• High school diploma or GED.
• Ability to obtain Security+ CE, SSCP, CCNA‑Security, or GSEC certification within six months of hire.

• Experience developing prompts, tools, and agents with LLMs.
• Experience with AWS Sage Maker, Lambda, API Gateway, DynamoDB, S3, and IAM.
• Experience with Kubernetes.
• Experience with Infrastructure‑as‑Code tools such as Helm and Terraform.
• Experience design and implementation of end‑to‑end automated data and ML pipelines in a Cloud environment.
• Experience with version control tools, including Git.
• Bachelor’s degree (preferred). Master’s degree a plus.

The projected compensation range for this position is $77,600.00 to $ (annualized USD). This estimate reflects typical salary for this role and is one component of Booz Allen’s total compensation package, which also includes various benefits.

Booz Allen provides a comprehensive benefits package that includes health, life, disability, financial, and retirement benefits, paid leave, professional development, tuition assistance, work‑life programs, and dependent care. Full‑time and part‑time employees working at least 20 hours a week are eligible for the full benefits program.

Remote:
Remote work may be required to work in person at a Booz Allen or customer facility on occasion. Hybrid:
Employees may be expected to work from a Booz Allen facility frequently as well as at the customer site. Onsite:
Work is primarily performed at a Booz Allen office or customer facility, collaborating directly with colleagues and customers.

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran, or any other status protected by applicable federal, state, local, or international law.