MLOps Engineer, Senior Security Clearance

Position: MLOps Engineer, Senior with Security Clearance
Job Number: R0227821 MLOps Engineer, Senior

The Opportunity:

Are you looking for an opportunity to make a difference and help build a system that will have a positive impact in 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 you, an experienced machine learning engineer, 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 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. Join us. The world can't wait. You Have:
* 4+ years of experience with Object
-Oriented Programming (OOP) , including in Python

* 4+ years of experience with developing containerized applications, including API design and authentication

* 3+ years of experience with developing software using cloud technologies, including AWS

* 3+ years of 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

* Top Secret clearance

* HS diploma or GED

* Ability to obtain a Security+ CE, SSCP, CCNA-Security, or GSEC certification within 6 months of hire date Nice If You Have:
* Experience developing prompts, tools, and agents with LLMs

* Experience with AWS Sage Maker, Lambda, API Gateway, Dynamo

DB, S3, and IAM

* Experience with Kubernetes

* Experience with IaC tools like 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 Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information;
Top Secret clearance 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.

Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability…