MLOps Engineer, Mid

MLOps Engineer, Mid 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: Experience with Object-Oriented Programming (OOP), including in Python Experience with developing containerized applications, including API design and authentication Experience with developing software using cloud technologies, including AWS 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 TS/SCI clearance with a polygraph 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 SageMaker, Lambda, API Gateway, DynamoDB, S3, 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 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; TS/SCI clearance with polygraph is required. 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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 and organizational requirements. The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date. 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. 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