Location: Aurora, Colorado, USA
Remote Work: Hybrid
Job Number: R0164212
AWS and Python MLOps Engineer, Mid
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 cloud 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 small 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. This position is a hybrid role with a combination of working at a Booz Allen office or client site and working remotely.
Empower change with us.
3+ years of experience with Python development
3+ years of experience with designing, developing, deploying, and testing in Amazon Web Services (AWS) and using tools, such as Lambda, API Gateway, S3, CloudFormation, and IAM permissions
Experience leveraging MLOps platforms and ML CI/CD workflows to manage datasets and model training, deployment, and monitoring
Knowledge of the Machine Learning Workflow
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
Nice If You Have:
Experience with using ML tools, such as SageMaker, Python, TensorFlow, scikit-learn, PyTorch, Kubeflow, MLflow, or similar frameworks
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
Experience leading a team of developers or converting requirements into technical documentation
Experience with an Agile release methodology
Knowledge of the ML life cycle and concepts to develop an MLOps ecosystem
Bachelor’s degree preferred; Master’s degree a plus
Security+ CE, SSCP, CCNA-Security, or GSEC Certification
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.
Build Your Career:
A challenging and dynamic work environment isn’t all we have to offer. When you join Booz Allen, you’ll have access to:
experts in virtually every field
a culture that focuses on supporting our employees
opportunities that provide stability while offering variety
You’ll also be exposed to a wealth of training resources through our Digital University, an online learning portal featuring more than 5000 functional and technical courses, certifications, and books. Build your technical skills through hands-on training on the latest tools and tech from our in-house experts. Pursuing certifications that directly impact your role? You may be able to take advantage of our tuition assistance, on-site bootcamps, certification training, academic programs, vendor relationships, and a network of professionals who can give you helpful tips. We’ll help you develop the career you want as you chart your own course for success.
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 $58,300.00 to $133,000.00 (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.
We’re an equal employment opportunity/affirmative action employer that empowers our people to fearlessly drive change – no matter their race, color, ethnicity, religion, sex (including pregnancy, childbirth, lactation, or related medical conditions), national origin, ancestry, age, marital status, sexual orientation, gender identity and expression, disability, veteran status, military or uniformed service member status, genetic information, or any other status protected by applicable federal, state, local, or international law.
Booz Allen / Equal Opportunity Employer
FVR05 SKUUU, Aurora, Colorado Aurora, Colorado ZC ZCCX