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Part Time Machine Learning Postdoc Jobs (NOW HIRING)

TripleTen

$40 - $150/hr

All roles are part-time: 10-15 hours per week. Requirements * 5+ years of experience in Data Science, Machine Learning, or ML Engineering, with a strong focus on supervised learning, time series ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103.90K - $136.80K/yr

Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Candidates hired to ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103.90K - $136.80K/yr

Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Candidates hired to ...

Mindrift

Machine Learning Developer (Freelance)

$90/hr

... to part-time, non-permanent projects. Ideally, contributors will have: * 5+ years of hands-on ... Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and ...

Mindrift

Freelance Machine Learning Engineer

$90/hr

... to part-time, non-permanent projects. Ideally, contributors will have: * 5+ years of hands-on ... Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and ...

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Part Time Machine Learning Postdoc information

What are the key skills and qualifications needed to thrive as a Part Time Machine Learning Postdoc, and why are they important?

To thrive as a Part Time Machine Learning Postdoc, you need a Ph.D. in a relevant field, strong research experience, and deep understanding of machine learning algorithms and statistical methods. Proficiency with programming languages like Python, ML frameworks (e.g., TensorFlow, PyTorch), and experience with data analysis tools is crucial. Excellent problem-solving, effective communication, and time management skills help you balance research demands and collaboration. These skills ensure impactful contributions to research projects, efficient workflow, and successful dissemination of findings.

How does working part-time as a Machine Learning Postdoc typically impact collaboration with research teams and project timelines?

Part-time Machine Learning Postdocs often collaborate closely with both faculty and full-time researchers, which requires clear communication and proactive scheduling to ensure smooth progress on shared projects. Balancing part-time hours may mean prioritizing specific tasks and being especially organized to keep projects on track. Many teams accommodate flexible work arrangements, but it's crucial to set expectations around availability and deliverables. Regular check-ins and use of collaborative tools can help maintain strong connections with the team and ensure that research milestones are met.

What is a Part Time Machine Learning Postdoc?

A Part Time Machine Learning Postdoc is a researcher who holds a postdoctoral position in the field of machine learning, but works fewer hours than a standard full-time appointment. These roles typically involve conducting advanced research, publishing papers, and contributing to academic or industry projects while allowing for flexibility in work hours. Such positions are ideal for those who may have other commitments, such as teaching, consulting, or personal responsibilities, and still want to further their research careers. The expectations and benefits may differ from full-time roles, but they offer valuable experience and networking opportunities in the rapidly evolving field of machine learning.

What is the difference between Part Time Machine Learning Postdoc vs Part Time Data Scientist?

AspectPart Time Machine Learning PostdocPart Time Data Scientist
Required CredentialsPhD in Machine Learning, Computer Science, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often prefers experience
Work EnvironmentAcademic research settings, universities, research labsIndustry companies, startups, corporate analytics teams
Employer & Industry UsageUniversities, research institutions, government agenciesTech firms, finance, healthcare, retail sectors
Common Search & Comparison IntentUnderstanding academic research roles in machine learningApplying machine learning techniques in industry projects

While both roles involve machine learning expertise, a Part Time Machine Learning Postdoc typically focuses on academic research, publishing papers, and advancing theoretical knowledge. In contrast, a Part Time Data Scientist applies machine learning models to solve practical industry problems, often working directly with business data and stakeholders.

More about Part Time Machine Learning Postdoc jobs
What cities are hiring for Part Time Machine Learning Postdoc jobs? Cities with the most Part Time Machine Learning Postdoc job openings:
What are the most commonly searched types of Machine Learning Postdoc jobs? The most popular types of Machine Learning Postdoc jobs are:
What states have the most Part Time Machine Learning Postdoc jobs? States with the most job openings for Part Time Machine Learning Postdoc jobs include:
What job categories do people searching Part Time Machine Learning Postdoc jobs look for? The top searched job categories for Part Time Machine Learning Postdoc jobs are:
Part Time Machine Learning Postdoc jobs near you
Infographic showing various Part Time Machine Learning Postdoc job openings in the United States as of May 2026, with employment types broken down into 100% Part Time. Highlights an 100% In-person job distribution.

Machine Learning Teaching Experts Part-time

TripleTen

On-site, Remote

$40 - $150/hr

Part-time

Posted 3 days ago

Job description

Description
Nebius Academy is an international online learning platform helping engineering teams master AI and cloud technologies. We build hands-on, industry-relevant programs for B2B audiences - combining deep technical expertise with real-world application. Our Machine Learning curriculum covers the full ML lifecycle: from foundational concepts and mathematical methods to supervised learning, time series forecasting, and numerical methods - applied to real business problems.
Who are we looking for? We are building a talent pool of experienced Data Scientists and ML practitioners for ongoing roles as Instructors, Authors, and Subject Matter Experts in our Machine Learning educational programs.
We are looking for specialists across the following areas: Machine Learning in Business, Basics of Machine Learning, Supervised Learning, Time Series in Machine Learning, Numerical Methods of Machine Learning, and adjacent ML engineering topics.
A strong candidate doesn't just know their stack deeply - they actively apply ML in real-world projects and can translate complex concepts into practical, teachable content. We prioritize hands-on experience with tools and workflows such as Scikit-learn, PyTorch, XGBoost, time series libraries (Prophet, statsmodels), ML experiment tracking (MLflow, W&B), feature engineering pipelines, or similar. The ability to teach others how to build and evaluate models in real business contexts is what sets our experts apart.
These are Talent Pool positions - we continuously review applications and build our roster of experts. This means there may not be an immediate opening at the time you apply, but strong candidates will be added to our talent pool and contacted as relevant opportunities arise.
You can join us on a part-time basis (~10-15h/week), contributing as an instructor leading live sessions and workshops, as a course author creating learning materials, or as a subject matter expert supporting curriculum development. Teaching sessions are compensated separately.
Compensation: $40-150/hour, depending on experience and format of collaboration.
Our selection process is fully asynchronous and designed to respect your time:
  1. Application Review - we evaluate your profile against our current needs
  2. Async Video Interview - a short self-recorded interview (10-15 minutes max)
  3. Test Assignment - approximately 1 hour to complete
  4. Talent Pool - finalists are added to our active roster of vetted experts
  5. Hiring Manager & Tech Expert Call - once a relevant position opens, we invite you to a live interview with our team
  6. Offer - we extend an offer for a relevant position upon successful completion of the process

Apply now - we review applications on an ongoing basis.
Please submit your resume in English.
What you will do
Available Roles
We are building a talent pool of Instructors, Authors, and Subject Matter Experts for our Machine Learning educational programs. We hire on an ongoing basis across the following specializations: Most in demand: ML in Business, Supervised Learning, Time Series in ML
Also relevant: Basics of Machine Learning, Numerical Methods of Machine Learning, and adjacent ML and data science topics
Depending on your expertise, you may:
  • Deliver live workshops and training sessions
  • Create educational content, assessments, and project-based learning materials
  • Design practical exercises, guides, prompts, and reference resources
  • Help define curriculum structure, learning objectives, and competency frameworks
  • Review content for technical accuracy and industry relevance
  • Share insights on AI tools, workflows, and emerging trends
  • Collaborate with instructional designers and curriculum teams to continuously improve learning outcomes
  • Support program updates based on learner feedback and market needs

Areas of involvement
  • Instructor - leads live sessions, workshops, and learner interactions.
  • Author - creates course content, lessons, assessments, and projects.
  • Subject Matter Expert - shapes curriculum strategy, competency frameworks, and program direction.

All roles are part-time: 10-15 hours per week.
Requirements
  • 5+ years of experience in Data Science, Machine Learning, or ML Engineering, with a strong focus on supervised learning, time series forecasting, or applied ML in business contexts
  • Strong knowledge of Python and the core ML stack: Scikit-learn, Pandas, NumPy, and familiarity with numerical methods and forecasting libraries
  • Hands-on experience building, deploying, and evaluating ML models in real-world environments, with measurable business impact
  • Strong ability to share knowledge through content creation, training, mentoring, facilitation, or public speaking, making complex ML concepts clear, practical, and engaging for learners
  • Ability to work independently with strong ownership and minimal supervision
  • Strong attention to detail
  • Availability to collaborate within European time zones
  • Ability to dedicate approximately 10-15 hours per week
  • Fluent English (written and spoken); Russian or Spanish is a strong plus
  • Background in ML advocacy, tech leadership, mentoring, conference speaking, or technical community engagement is a plus

Subject Matter Expert
  • Strong expertise in Machine Learning, Data Science, or ML Engineering
  • Ability to evaluate real-world ML tools, modeling approaches, and workflows, distinguishing practical solutions from hype
  • Experience creating competency maps, skill frameworks, learning roadmaps, or curriculum structures
  • Ability to review technical learning content and provide structured feedback

What we can offer you
  • The opportunity to create impactful content while maintaining your primary job: Share your expertise without leaving your current role
  • Competitive hourly rate of $40-$85 USD for flexible part-time collaboration with significant impact and an amazing team!
  • Remote cooperation with a schedule convenient for both you and the team: We don't focus on micromanagement
  • Cross-cultural experience: Become part of an international team and connect with professionals from diverse backgrounds
  • Meaningful impact: Share your knowledge and help experienced engineers advance their skills through high-quality educational content
  • Participation in innovative projects: Contribute to shaping the future of programming education and AI adoption
  • Professional growth: Receive feedback and develop your skills as a technical content creator and thought leader

Apply