MLOps Engineer

Booz Allen Hamilton•Chantilly, VA

1d•Onsite

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. 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 ML across the enterprise. You’ll implement continuous integration and continuous deployment (CI/CD) into development, testing, and production environments. This is an opportunity to broaden your skillset into areas like Agile development, cloud-based development, containerization, and serverless while developing software that will improve national security. As an ML 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. Join us. The world can’t wait.

Requirements

2+ years of experience with Object-Oriented Programming (OOP), including in Python
2+ years of experience developing containerized applications, including API design and authentication
2+ years of experience developing software using cloud technologies, including AWS
2+ years of experience leveraging MLOps platforms and ML CI/CD workflows to manage datasets and model training, deployment, and monitoring
2+ 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 and 2+ years of experience in AI/ML engineering, or 4+ years of experience in AI/ML engineering in lieu of a degree
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 and architect an MLOps platform in the cloud.
Streamline the development life cycle from development to production.
Build and maintain cloud software and infrastructure that supports ML across the enterprise.
Implement continuous integration and continuous deployment (CI/CD) into development, testing, and production environments.
Identify new opportunities to build solutions and architecture to help customers meet their toughest challenges.