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Part Time Machine Learning Researcher Jobs in Massachusetts

TripleTen

$40 - $150/hr

Our Machine Learning curriculum covers the full ML lifecycle: from foundational concepts and ... You can join us on a part-time basis (~10-15h/week), contributing as an instructor leading live ...

TripleTen

$40 - $150/hr

Our Mathematics for Machine Learning curriculum bridges the gap between mathematical theory and ... You can join us on a part-time basis (~10-15h/week), contributing as an instructor leading live ...

Varsity Tutors

Statistics Graduate Level Tutor

Lynn, MA · Remote

$40/hr

Emphasizes theoretical foundations and connects advanced statistics to biostatistics, econometrics, and machine learning research applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

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Part Time Machine Learning Researcher information

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

To thrive as a Part Time Machine Learning Researcher, you need a solid background in mathematics, statistics, and programming, often demonstrated through academic coursework or relevant research experience. Familiarity with programming languages like Python or R, machine learning libraries (e.g., TensorFlow, PyTorch), and version control systems such as Git is typically required. Strong analytical thinking, curiosity, and effective communication skills help in interpreting data and collaborating with research teams. These competencies enable researchers to design, implement, and present innovative solutions to complex problems in machine learning.

How do part-time machine learning researchers typically balance independent work with collaboration within their research teams?

Part-time machine learning researchers often have flexible schedules, which means they need to be proactive in communicating with their teams and managing project timelines. While much of the research work can be done independently—such as data analysis, model development, and literature review—regular meetings and updates are essential to stay aligned with the team's goals. Many teams use collaborative platforms and version control systems to facilitate seamless contributions from part-time members. Clear documentation and open communication help ensure that part-time researchers can effectively integrate their work with the broader project and contribute meaningfully despite reduced hours.

What does a Part Time Machine Learning Researcher do?

A Part Time Machine Learning Researcher typically works on developing, testing, and improving machine learning models and algorithms, often as part of a research team or academic project. Their responsibilities may include data analysis, implementing machine learning techniques, conducting literature reviews, and contributing to research publications or presentations. Since the role is part-time, they usually work flexible hours and may balance these duties with other commitments such as studies or a different job. The position is ideal for students, professionals seeking experience, or those who wish to contribute to research while managing other responsibilities.

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

AspectPart Time Machine Learning ResearcherData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fieldsOften requires a bachelor's or master's in data science, statistics, or related areas
Work EnvironmentResearch-focused, often in academic or R&D settings, with emphasis on developing new algorithmsBusiness-focused, working with large datasets to generate insights and support decision-making
Industry UsageCommon in research institutions, universities, and R&D departmentsWidely used across industries like finance, healthcare, tech, and marketing

While both roles involve working with machine learning, a Part Time Machine Learning Researcher primarily focuses on developing new algorithms and research, often in academic or research settings. In contrast, a Data Scientist applies machine learning techniques to analyze data and solve business problems. The roles share similar credentials but differ in work environment and industry application.

What are popular job titles related to Part Time Machine Learning Researcher jobs in Massachusetts? For Part Time Machine Learning Researcher jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Part Time Machine Learning Researcher jobs in Massachusetts look for? The top searched job categories for Part Time Machine Learning Researcher jobs in Massachusetts are:
What cities in Massachusetts are hiring for Part Time Machine Learning Researcher jobs? Cities in Massachusetts with the most Part Time Machine Learning Researcher job openings:
Part Time Machine Learning Researcher jobs near you

Part-time Experts - Machine Learning (B2B, Nebius Academy)

TripleTen

On-site, Remote

$40 - $150/hr

Part-time

This job post has expired today. Applications are no longer accepted.

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
Instructor You will lead live, hands-on training sessions for experienced data practitioners, helping them apply machine learning concepts and tools to real-world business problems.
  • Conduct live, interactive training sessions and workshops
  • Prepare practical workshop scenarios and training materials in collaboration with our Instructional Designer
  • Develop reusable materials: model-building exercises, prompt libraries, challenge tasks, and reference guides
  • Work with the curriculum team to ensure alignment between asynchronous and live content
  • Communicate with students during Q&A sessions
  • Review and incorporate learner feedback to continuously improve session design

Author You will create the core educational content for our ML courses - from structure and learning objectives to lessons, assessments, and final projects.
  • Collaborate with us to define the course structure and learning objectives for each module
  • Create clear, concise, and comprehensive content: lessons, manuals, guides, session outlines, and assessments
  • Prepare content in multiple formats: text, draft slides, and screencasts
  • Participate as a speaker in learning videos
  • Design the final project for the course
  • Work iteratively with instructional designers to improve content quality
  • Ensure all content meets industry standards and aligns with course objectives
  • Contribute to content updates based on student feedback analysis
  • Optional: participate as an instructor in live sessions - compensated separately

Subject Matter Expert You will shape the strategic direction of our ML curriculum, ensuring our programs reflect real industry needs and the latest developments in machine learning and data science.
  • Define topic priorities for ML learning programs targeting data scientists, ML engineers, and adjacent technical roles
  • Decompose ML and data science skills into competency maps, mastery frameworks, and learning roadmaps
  • Review course structures and content for technical accuracy, practical relevance, and alignment with learning outcomes
  • Act as an internal authority for the Curriculum team - translating market needs and ML trends into program strategy
  • Support the selection and evaluation of external authors and experts
  • Monitor emerging ML tools, frameworks, and workflows; convert insights into recommendations for new or updated programs

All roles are part-time: 10-15 hours per week.
Requirements
Subject Matter Expert
  • Strong hands-on technical expertise in machine learning, data science, or ML engineering
  • Ability to evaluate real-world ML tools, modeling approaches, and workflows - and distinguish practical solutions from hype
  • Experience structuring complex ML knowledge into competency maps, frameworks, skill decompositions, or curriculum logic
  • Ability to review technical learning content critically and provide clear, structured feedback to authors and internal stakeholders
  • Seniority level that allows autonomous work after onboarding, with strong ownership and minimal supervision
  • Strong communication skills and ability to explain complex technical topics clearly to mixed stakeholders
  • Availability to collaborate within European time zones
  • Fluent English (written and spoken); Russian or Spanish is a strong plus

Author
  • 5+ years of professional experience in data science or ML engineering, with a strong focus on supervised learning, time series, or applied ML in business contexts
  • Solid knowledge of Python and core ML stack: Scikit-learn, Pandas, NumPy, and familiarity with numerical methods and forecasting libraries
  • Hands-on experience building and deploying ML models in real-world settings - with concrete implementation cases and measurable impact
  • Proven track record in engineering advocacy, tech leadership, conference speaking, or mentoring
  • Strong desire to share knowledge and explain complex concepts in a clear, comprehensible way
  • Ability to work independently and take ownership of a content area
  • Strong attention to detail
  • Availability to dedicate approximately 10 hours per week to collaboration
  • Fluent English (written and spoken); Russian or Spanish is a strong plus

Instructor
  • 5+ years of experience in data science or ML engineering, with a strong focus on supervised learning, time series, or applied ML in business contexts
  • Solid knowledge of Python and core ML stack: Scikit-learn, Pandas, NumPy, and familiarity with numerical methods and forecasting libraries
  • Hands-on experience building and deploying ML models in real-world settings - with concrete implementation cases and measurable impact
  • Ability to translate complex ML concepts into actionable, engaging learning experiences for professional audiences
  • Confident, collaborative, and audience-oriented facilitation style
  • Background in ML advocacy, tech leadership, or data science mentorship is a strong plus
  • Strong preparation habits and time management; able to commit 10-15 hours per week
  • Fluent English (written and spoken); Russian or Spanish is a strong plus

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