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Part Time Mlops Jobs (NOW HIRING)

Weekday AI

Insurance Underwriting AI Expert

$100 - $120/hr

... 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 ...

Uottawa

APTPUO-Fall 2026-DTI6302 F

Campus, IL

$239.47/hr

Professeur a temps-partiel regulier / Regular Part-Time Professor Date Posted (YYYY/MM/DD): 2026/05 ... They should have hands-on experience applying the latest MLOps techniques, such as continuous ...

TEGNA Inc.

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 ...

TEGNA

AI Engineer

Mclean, VA · On-site +1

Knowledge of MLOps best practices. * Experience with vector databases and embeddings. * Familiarity ... Our 401(k) program offers full, part-time and temporary employees the opportunity to contribute ...

Booz Allen Hamilton, Inc.

AI Developer

San Antonio, TX · On-site

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.
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Part Time Mlops jobs near you
Infographic showing various Part Time Mlops job openings in the United States as of May 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution.
Data Scientist, Upstream Development

Data Scientist, Upstream Development

ExxonMobil

Spring, TX

Part-time

Medical, Dental, Vision, Life, Retirement

Posted 22 days ago

ExxonMobil rating

6.1

Company rating: 6.1 out of 10

Based on 220 frontline employees who took The Breakroom Quiz

57th of 74 rated oil and gas companies

Job description

About us

At ExxonMobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.

The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies. 

We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs. Learn more about our What and our Why and how we can work together.

What you will do

Lead the design, development, and deployment of advanced AI/ML solutions for upstream oil & gas subsurface & well operations such as physics-informed Machine Learning (ML) and production optimization.  You will work end-to-end from problem framing and experimentation through production and sustainment partnering with engineers and business stakeholders to deliver scalable, reliable, and impactful solutions.

What role will you play in the team
  • Lead end-to-end delivery of AI/ML solutions: scoping, modeling, evaluation, deployment, and monitoring.
  • Collaborate with cross-functional teams to translate business problems into mathematical frameworks.
  • Build solutions in one or more domains listed above, applying best practices for data quality, explainability, and governance.
  • Develop GenAI applications (chatbots, copilots, multi-agent workflows) and/or time series, optimization, or commercial analytics models.
  • Ensure production readiness through MLOps practices (CI/CD, MLflow, monitoring, cost optimization).
  • Mentor peers and contribute to internal AI capability building.
About you

Desired Skills

  • 5+ years of direct experience delivering production AI/ML solutions.
  • Experience applying data science to upstream oil & gas workflows, including exploration, drilling and reservoir management; analyzing well logs, seismic data, and production metrics to support operational and strategic decisions
  • Strong foundations in statistics, probability, and algorithm design.
  • Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn); experience with Databricks/Spark.
  • Familiarity with GenAI frameworks (LangChain, Promptflow) and/or optimization libraries.
  • Experience with MLOps, model governance, and explainable AI techniques (e.g., SHAP, LIME).
  • Excellent communication and collaboration skills.

Preferred Knowledge/Skills

  • Cloud platforms (Azure ML, Azure OpenAI, Databricks).
  • Knowledge graphs, hybrid search/RAG, and semantic technologies.
  • Agile development and software engineering best practices.

Educational Background Recommended

  • Master’s or PhD in Data Science, Computer Science, Engineering, Applied Math, or related field.
Your benefits

An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance, and life.
 

We offer you: 
 

  • Pension Plan: Enrollment is automatic and at no cost to you. The basic benefit is a monthly annuity to be paid to you in retirement for the rest of your life. 
  • Savings Plan: You can contribute between 6% and 20% of your pay and are encouraged to enroll right away. If you contribute at least 6% to your savings plan, the Company will contribute a 7% match. 
  • Workplace Flexibility: We have several programs such as “Flex your Day”, providing ad-hoc flexibility around when and where you work, as well as longer-term programs such as leaves of absence and part-time work.
  • Comprehensive medical, dental, and vision plans. 
  • Culture of Health: Programs and resources to support your wellbeing. 
  • Employee Health Advisory Program: Provides confidential professional counseling for you and your family, including tools and resources promoting mental health and resiliency at no additional cost to you. 
  • Disability Plan: Income replacement for when you cannot work due to illness or injury occurring on or off the job. Enrollment is automatic and at no cost to you.
     

More information on our Company’s benefits can be found at  www.exxonmobilfamily.com.
 

Please note benefits may be changed from time to time without notice, subject to applicable law.

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Alternate Location:  

Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship. 

Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.

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