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. 

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. 

You Have:

• 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 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. 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 or customer facility, in alignment with your leadership's expectations and the needs of the role.
• Onsite: If this position is listed as onsite, work will primarily be performed full-time at a 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.