The Opportunity:

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. 

You Have: 

• 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 If You Have: 

• 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 

Clearance: 

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. 

Compensation

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Identity Statement

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.

Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

• Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.

• Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.

• Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination

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.