Booz Allen Hamilton-posted 1 day ago
Full-time • Mid Level
Bethesda, MD
1-10 employees

MLOps Engineer The Opportunity: Are you looking for an opportunity to make a difference and help build a system that will have a positive impact on public health? What if you could find a position that is tailor-made for your mix of development, engineering, and analytics skills? 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 build and configure 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 lifecycle from development to production. You’ll be working with a collaborative Agile development team to build and maintain cloud sof tware and infrastructure that supports ML across the enterprise. You’ll implement continuous integration and continuous deployment ( CI / CD ) 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 sof tware that will improve public health. As an ML engineer, you’ll identify new opportunities to build solutions and architecture to help your customers meet their toughest challenges. Work with us to solve real-world challenges and define an ML strategy for public health, and protect America from health, safety, and security threats.

  • Build, configure, and maintain a robust MLOps platform in the cloud to streamline the development lifecycle from development to production, ensuring efficient deployment of ML models.
  • Design and implement CI/CD workflows to automate the testing, integration, and deployment of ML models in development, testing, and production environments.
  • Work closely with an Agile development team, leveraging collaborative approaches to develop, deploy, and maintain cloud-based sof tware and infrastructure supporting enterprise-wide ML initiatives.
  • Enhance and manage ML lifecycles, including data management, model training, deployment, and monitoring, to ensure seamless integration and operation within production environments.
  • Develop containerized applications, focusing on API design and authentication, to ensure scalable and secure deployment of ML models across cloud environments.
  • Utilize distributed and cloud technologies such as Azure and Databricks to efficiently manage data and ML workflows, optimizing performance and scalability.
  • Identify new opportunities to design and implement end-to-end automated data and ML pipelines, leveraging cloud services, containerization, and serverless architectures to meet the client’s toughest challenges.
  • Continuously evaluate and integrate new tools and technologies such as Kubernetes, version control systems like Git, and other cloud services such as Azure Data Lake Services or Data Factory, to enhance the MLOps ecosystem and improve development workflows.
  • 4+ years of experience with Object-Oriented Programming ( OOP )
  • 3+ years of experience developing sof tware using distributed and cloud technologies, including Azure or Databricks
  • 3+ years of experience leveraging MLOps platforms and ML CI / CD workflows to manage datasets and model training, deployment, and monitoring
  • Experience developing containerized applications, including API design and authentication
  • Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem
  • Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
  • Bachelor's degree
  • Experience with Python and PySpark
  • Experience with Azure Data Lake Services, Data Factory, Synapse, Purview, EntraID, or other cloud services
  • Experience with Kubernetes
  • 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
  • health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care
  • recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values
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