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 you, an experienced machine learning engineer, 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 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 public health. As a machine learning 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.

What You’ll Work On:

• Build, configure, and maintain a robust MLOps platform in the Cloud to streamline the development lifecycle from development to production, ensuring efficient deployment of machine learning models.

• Design and implement continuous integration and continuous deployment (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 software and infrastructure supporting enterprise-wide machine learning 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 machine learning 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.

Join us. The world can’t wait.

You Have:

• 4+ years of experience with Object-Oriented Programming (OOP), including in Python or PySpark

• 3+ years of experience developing software using distributed and cloud technologies, including Azure and Databricks

• 3+ years of experience leveraging MLOps platforms and Machine Learning (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

• Public Trust

• Bachelor's degree

Nice If You Have:

• 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

Vetting:

Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client; Public Trust determination 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 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 application process, 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.

Work Model
Our people-first culture prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely.

• If this position is listed as remote or hybrid, you’ll periodically work from a Booz Allen or client site facility.
• If this position is listed as onsite, you’ll work with colleagues and clients in person, as needed for the specific 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.