MLOps Engineer, Mid

Overview

The MLOps Engineer role focuses on designing and building an MLOps platform in the Cloud to shorten the time to production for machine learning capabilities in support of mission-critical operations in the intelligence community. You will contribute to streamlining the development life cycle from development to production, working with an Agile team to build and maintain cloud software and infrastructure that supports ML across the enterprise.

You will implement continuous integration and deployment to development, testing, and production environments and grow skills in Agile development, cloud-based development, containerization, and serverless technologies while developing software that improves national security.

As an MLOps Engineer on our team, you ll use your development experience to streamline our development life cycle from development to production. You ll be working with a collaborative Agile development team to build and maintain Cloud software and infrastructure that supports machine learning across the enterprise. You ll implement continuous integration and deployment to development, testing, and production environments.

This is an opportunity to broaden your skill set into areas like Agile development, Cloud-based development, containerization, and serverless while developing software that will improve national security. As a machine learning engineer, you ll identify new opportunities to build solutions and architecture to help your customers meet their toughest challenges. Join our team as we build tools to transform the future of the IC.

• Experience with Object-Oriented Programming (OOP), including in Python
• Experience with developing containerized applications, including API design and authentication
• Experience with developing software using cloud technologies, including AWS
• Experience with leveraging MLOps platforms and Machine Learning (ML) CI/CD workflows to manage datasets and model training, deployment, and monitoring
• Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem
• TS/SCI clearance with a polygraph
• HS diploma or GED
• Ability to obtain a Security+ CE, SSCP, CCNA-Security, or GSEC certification within 6 months of hire date

• 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 IaC tools such as Helm and Terraform
• Experience with design and implementation, including building, containerizing, and deploying end-to-end automated data and ML pipelines, within a Cloud environment
• Experience with version control tools, including Git
• Bachelor s degree preferred;
  Master s degree a plus
• Security+ CE, SSCP, CCNA-Security, or GSEC Certification

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance with polygraph is required.

Salary and benefits information:
The projected compensation range for this position is $77,600 to $176,000 (annualized USD). The posting notes Booz Allen s total compensation package, benefits, and work-life programs. This posting will close within 90 days from the Posting Date.

All qualified applicants will receive consideration for employment without regard to disability, veteran status, or any other status protected by applicable law.