MLOps Engineer

Booz Allen Hamilton•Chantilly, VA

22h•Remote

About The Position

Are you looking for an opportunity to make a difference and help build a system that will have a positive impact on the intelligence community (IC)? What if you could find a position that is tailor-made for your mix of development, engineering, and analytics? Efficient development teams make the most of their time by limiting the activities that take developers and data scientists away from writing their code. That’s why we need an experienced machine learning (ML) engineer like you to help us design and architect an MLOps platform in the cloud that shortens the time it takes to get new capabilities from development to production, to support mission-critical operations. On our Agile, highly collaborative team, you will help design, build, and maintain cloud-based software and infrastructure that powers enterprise-wide ML. You will implement and refine CI/CD workflows across development, test, and production environments. This position gives you the opportunity to expand your skills in Agile development, cloud-native engineering, containerization, and serverless technologies all while building systems that strengthen national security. As an ML engineer, you will also identify opportunities to architect new solutions, enhance existing pipelines, and guide mission partners through their toughest technical challenges. Join us as we build tools that transform the future of the IC. Join us. The world can’t wait.

Requirements

5+ years of experience with Object-Oriented Programming (OOP), including in Python
5+ years of experience developing containerized applications, including API design and authentication
5+ years of experience developing software using cloud technologies, including AWS
5+ years of experience leveraging MLOps platforms and ML CI/CD workflows to manage datasets and model training, deployment, and monitoring
5+ years of experience developing prompts, tools, and agents with LLMs
Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem
TS/SCI clearance with a polygraph
Bachelor’s degree in CS or Software Engineering
Ability to obtain a Security+ CE, SSCP, CCNA-Security, or GSEC Certification within 6 months of hire date

Nice To Haves

Experience with AWS SageMaker, Lambda, API Gateway, DynamoDB, S3, Bedrock, 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
Master’s degree
Security+ CE, SSCP, CCNA-Security, or GSEC Certification

Responsibilities

Design, build, and maintain cloud-based software and infrastructure that powers enterprise-wide ML.
Implement and refine CI/CD workflows across development, test, and production environments.
Identify opportunities to architect new solutions.
Enhance existing pipelines.
Guide mission partners through their toughest technical challenges.