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Summer Machine Learning Teaching Jobs (NOW HIRING)

TripleTen

$40 - $150/hr

Our Machine Learning curriculum covers the full ML lifecycle: from foundational concepts and ... The ability to teach others how to build and evaluate models in real business contexts is what sets ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Design tools and interfaces for interactive machine learning and teaching. * Research and development on cutting-edge machine learning technologies. Qualifications and Skills: * Graduate degree in ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Design tools and interfaces for interactive machine learning and teaching. * Research and development on cutting-edge machine learning technologies. Qualifications and Skills: * Graduate degree in ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

Hang raised a $16 million Series A led by Paradigm last summer, with participation from Tiger ... This person will implement and develop machine learning models to enhance our platform ...

Jane Street

Machine Learning Educator

New York, NY · On-site

About the Position We're looking for an experienced and skilled educator to help us teach people at Jane Street about machine learning. Machine learning is a critical pillar of Jane Street's global ...

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All JobsSummer Machine Learning Teaching Jobs

Summer Machine Learning Teaching information

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$23K

$53.5K

$99.5K

How much do summer machine learning teaching jobs pay per year?

As of May 31, 2026, the average yearly pay for summer machine learning teaching in the United States is $53,476.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,000.00 and $60,000.00 per year, depending on experience, location, and employer.

What is the difference between Summer Machine Learning Teaching vs Summer Data Science Teaching?

AspectSummer Machine Learning TeachingSummer Data Science Teaching
Required CredentialsBackground in machine learning, programming, and statisticsKnowledge of data analysis, statistics, and programming
Work EnvironmentEducational settings, workshops, or bootcampsEducational or training programs, workshops, or bootcamps
Employer & Industry UsageUniversities, tech companies, educational platformsUniversities, research institutions, tech companies
Comparison Search IntentUnderstanding roles related to machine learning educationUnderstanding roles related to data science education

Summer Machine Learning Teaching focuses on instructing students in machine learning algorithms, models, and programming, often requiring a strong background in mathematics and programming. Summer Data Science Teaching covers broader data analysis skills, including statistics, data visualization, and programming. Both roles involve educational settings and are used by universities and tech companies, but they emphasize different technical areas.

More about Summer Machine Learning Teaching jobs
What cities are hiring for Summer Machine Learning Teaching jobs? Cities with the most Summer Machine Learning Teaching job openings:
What are the most commonly searched types of Machine Learning Teaching jobs? The most popular types of Machine Learning Teaching jobs are:
What states have the most Summer Machine Learning Teaching jobs? States with the most job openings for Summer Machine Learning Teaching jobs include:
What job categories do people searching Summer Machine Learning Teaching jobs look for? The top searched job categories for Summer Machine Learning Teaching jobs are:
Summer Machine Learning Teaching jobs near you
Infographic showing various Summer Machine Learning Teaching job openings in the United States as of May 2026, with employment types broken down into 62% Full Time, 36% Part Time, and 2% Contract. Highlights an 82% Physical, and 18% Remote job distribution, with an average salary of $53,476 per year, or $25.7 per hour.

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