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Part Time Mlops Jobs (NOW HIRING)

AI/ML Engineer, Senior

Dayton, OH · On-site

$99K - $225K/yr

You will contribute end-to-end, spanning data processing, model development, MLOps, and integration ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

AI Engineer

Reston, VA · On-site

$99K - $225K/yr

Bachelor's degree Nice If You Have: * Experience collaborating with MLOps, DevOps, and ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

AI Engineer

Reston, VA · On-site

$99K - $225K/yr

Bachelor's degree Nice If You Have: * Experience collaborating with MLOps, DevOps, and ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Scientist, Mid

Reston, VA · On-site

$77K - $176K/yr

Experience with GenAI tech and MLOps * Active TS/SCI clearance; willingness to take a polygraph ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

AI/ML Engineer, Mid

Dayton, OH · On-site

$77K - $176K/yr

Experience with ML engineering and MLOps, including model versioning, CI/CD for ML, monitoring ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

... Type: Part-time / Contract Location: US, UK, Canada, France, Portugal (remote) We are seeking a ... Experience with AI model deployment and MLOps practices. * Knowledge of regulatory frameworks ...

Director, AI & Automation

New York, NY · On-site

$175K - $200K/yr

Proficiency in MLOps, containerization (Docker, Kubernetes), and Infrastructure as Code (Terraform ... Our 401(k) program offers full, part-time and temporary employees the opportunity to contribute ...

Experience implementing MLOps or DevSecOps practices such as CI/CD, containerization, automated ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

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Part Time Mlops information

What are the key skills and qualifications needed to thrive as a Part Time MLOps Engineer, and why are they important?

To thrive as a Part Time MLOps Engineer, you need a solid background in machine learning concepts, software engineering, and cloud infrastructure, often supported by a relevant degree or certifications. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and cloud platforms such as AWS, Azure, or GCP is essential. Strong problem-solving, collaboration, and communication skills help you work effectively with data scientists and developers. Mastery of these areas ensures the efficient deployment, scaling, and maintenance of machine learning models in production environments.

What is the difference between Part Time Mlops vs Data Engineer?

AspectPart Time MlopsData Engineer
CredentialsRelevant certifications in MLOps, cloud platforms, programmingData management, SQL, cloud certifications
Work EnvironmentRemote or flexible, project-basedOffice or remote, infrastructure-focused
Industry UsageAI/ML projects, deployment pipelinesData pipelines, database management
Search & Comparison IntentUnderstanding MLOps roles, part-time opportunitiesData infrastructure, engineering roles

Part Time Mlops roles focus on deploying and maintaining machine learning models, often requiring cloud and automation skills, while Data Engineers build and manage data pipelines and infrastructure. Both roles are essential in data-driven organizations but differ in scope and daily tasks.

What are part-time MLOps jobs?

Part-time MLOps jobs involve working reduced hours on tasks related to machine learning operations. MLOps professionals help manage and automate the deployment, monitoring, and maintenance of machine learning models in production environments. These roles may include responsibilities like setting up CI/CD pipelines for ML models, managing cloud infrastructure, monitoring model performance, and collaborating with data scientists. Part-time roles are ideal for those seeking flexible work schedules or supplementary income while still contributing to the development and operationalization of AI solutions.

What are some common challenges faced by part-time MLOps professionals, and how can they be managed effectively?

Part-time MLOps professionals often face the challenge of balancing project continuity with limited working hours. Coordination with full-time data scientists and engineers can be demanding, especially when aligning on deployment schedules or troubleshooting issues. To manage these challenges, clear communication, thorough documentation, and use of collaborative tools are crucial. Regular check-ins with the team and setting realistic expectations for deliverables can also help ensure smooth workflow and project progress.
More about Part Time Mlops jobs
What cities are hiring for Part Time Mlops jobs? Cities with the most Part Time Mlops job openings:
What are the most commonly searched types of Mlops jobs? The most popular types of Mlops jobs are:
Infographic showing various Part Time Mlops job openings in the United States as of June 2026, with employment types broken down into 100% Part Time. Highlights an 100% Remote job distribution.
MLOps Engineer, Mid

MLOps Engineer, Mid

Booz Allen Hamilton, Inc.

Alexandria, VA • On-site

$77K - $176K/yr

Full-time, Part-time

Medical, Life, Retirement, PTO

Posted 20 days ago


Booz Allen Hamilton rating

8.8

Company rating: 8.8 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

9th of 57 rated business consultants


Job description


Remote Work:
No
Job Number:
R0241240
Location:
Chantilly,VA,US
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Additional Locations:
  • Alexandria, Virginia, USA
  • Annapolis Junction, Maryland, USA
  • Aurora, Colorado, USA

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, and monitoring
  • Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem
  • 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 date

Nice If You Have:
  • Experience developing prompts, tools, and agents with LLMs
  • Experience with AWS SageMaker, Lambda, API Gateway, DynamoDB, S3, and IAM
  • Experience with Kubernetes
  • Experience with IaC tools such as Helm and Terraform
  • 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
  • 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; TS/SCI clearance with polygraph 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 hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. 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.
Candidate AI Usage Policy
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.
Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.
  • Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
  • Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.
  • Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the 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

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Booz Allen Hamilton is a leading provider of management and technology consulting services to the US government in defense, intelligence, and civil markets. Headquartered in McLean, Virginia, the firm also serves major corporations, institutions, and not-for-profit organizations. Founded in 1914 by Edwin G. Booz, the company has a long-standing tradition of helping clients achieve success by delivering a wide range of consulting services that include strategic planning, human capital and learning, communication, systems development, and others. The company's mission is to empower people to change the world, and it has a reputation for maintaining the highest standards of integrity and-excellence.

Industry

It services

Company size

10,000+ Employees

Headquarters location

McLean, VA, US

Year founded

1914