Booz Allen
MLOpsEngineer,Mid
Neural analysis suggests this role is
optimal for Mid candidates.
“MLOps Engineer, Mid at Booz Allen. Skills: MLOps, Cloud, Machine Learning, DevOps. Design MLOps platform. Architect MLOps platform”
What You'll Achieve.
Shorten time to production; Improve national security
Industry & Context.
Troubleshooting; Root cause analysis
TS/SCI clearance with polygraph, On camera during interviews
What They're Looking For.
Must Have
Experience with Object-Oriented Programming, Experience with Python, Experience developing containerized applications, Experience with API design, Experience with authentication, Experience developing software using cloud technologies, Experience with AWS, Experience leveraging MLOps platforms, Experience with Machine Learning CI/CD workflows, Knowledge of the ML lifecycle, Knowledge of ML concepts, TS/SCI clearance with polygraph, HS diploma or GED, Ability to obtain Security+ CE, Ability to obtain SSCP, Ability to obtain CCNA-Security, Ability to obtain GSEC certification within 6 months
Nice to Have
Experience developing prompts with LLMs, Experience developing tools with LLMs, Experience developing agents with LLMs, Experience with AWS SageMaker, Experience with AWS Lambda, Experience with AWS API Gateway, Experience with AWS DynamoDB, Experience with AWS S3, Experience with AWS IAM, Experience with Kubernetes, Experience with Helm, Experience with Terraform, Experience building automated data pipelines, Experience containerizing automated data pipelines, Experience deploying automated data pipelines, Experience building automated ML pipelines, Experience containerizing automated ML pipelines, Experience deploying automated ML pipelines, Experience with Git, Bachelor's degree, Master's degree, Security+ CE Certification, SSCP Certification, CCNA-Security Certification, GSEC Certification
What You'll Do.
Design MLOps platform
Architect MLOps platform
Streamline development life cycle
Maintain Cloud software
Support machine learning
Implement continuous integration
Implement continuous deployment
Identify new opportunities
How You'll Work.
Team & Collaboration
Collaborative Agile development team
Process & Methodology
Agile development
Full Job Description
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,
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