채용
Benefits & Perks
•Healthcare
•401k
•Learning
•Remote Work
Required Skills
Python
Object-Oriented Programming
AWS
Containerization
MLOps
CI/CD
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:
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Experience with Object-Oriented Programming (OOP), including in Python
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Experience with developing containerized applications, including API design and authentication
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Experience with developing software using cloud technologies, including AWS
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Experience with leveraging MLOps platforms and Machine Learning (ML) CI/CD workflows to manage datasets and model training, deployment, and monitoring
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Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem
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Top Secret clearance
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HS diploma or GED
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Ability to obtain a Security CE, SSCP, CCNA-Security, or GSEC certification within 6 months of hire date
Nice If You Have:
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Experience developing prompts, tools, and agents with LLMs
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Experience with AWS Sage Maker, Lambda, API Gateway, DynamoDB, S3, and IAM
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Experience with Kubernetes
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Experience with Ia
C tools like Helm and Terraform:
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Experience with design and implementation, including building, containerizing, and deploying end-to-end automated data and ML pipelines, within a Cloud environment
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Experience with version control tools, including Git
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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; Top Secret clearance 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.
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About Booz Allen Hamilton

Booz Allen Hamilton
PublicSpecializing in digital transformation and artificial intelligence.
10,001+
Employees
McLean
Headquarters
Reviews
3.5
5 reviews
Work Life Balance
2.5
Compensation
3.0
Culture
2.8
Career
2.5
Management
2.0
35%
Recommend to a Friend
Pros
Great reputation in federal sector
Hybrid work options available
Established teams and processes
Cons
Poor hiring and recruitment process
Job security concerns with contract-based work
Work-life balance issues
Salary Ranges
34 data points
Junior/L3
L2
L3
L4
L5
L6
Mid/L4
Senior/L5
Junior/L3 · Data Engineer
1 reports
$149,500
total / year
Base
$115,000
Stock
-
Bonus
-
$149,500
$149,500
Interview Experience
7 interviews
Difficulty
2.7
/ 5
Duration
21-35 weeks
Offer Rate
43%
Experience
Positive 29%
Neutral 28%
Negative 43%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Interview
4
Hiring Manager Interview
5
Team Interview
6
Offer
Common Questions
Technical Knowledge
Behavioral/STAR
Past Experience
System Design
Culture Fit
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