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Part Time Machine Learning Postdoc Jobs in Massachusetts

TripleTen

$152K/yr

We're looking for the person who brings an AI and Machine Learning curriculum to life for students: hosts the live sessions, reviews the work, runs the model and system review boards, and sets the ...

YO AI Labs

AI Data Scientist Expert - Remote

Boston, MA · Remote

$100 - $200/hr

Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

YO AI Labs

AI Data Science Expert - Remote

Boston, MA · Remote

$100 - $200/hr

Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

YO AI Labs

AI Data Scientist Expert - Remote

Boston, MA · Remote

$100 - $200/hr

Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

YO AI Labs

AI Data Science Expert - Remote

Boston, MA · Remote

$100 - $200/hr

Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

Boston Ski + Tennis

Service Associate

Westborough, MA · On-site

$16 - $20/hr

Westborough MA, Boston Ski and Tennis is hiring part-time service teammates for the upcoming season ... best machines * Learning and mastering ski binding adjustments, leveraging training from our ...

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All JobsMachine Learning Postdoc JobsPart Time Machine Learning Postdoc JobsPart Time Machine Learning Postdoc Jobs in Massachusetts

Part Time Machine Learning Postdoc information

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 are the key skills and qualifications needed to thrive as a part time machine learning postdoc?

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 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.

What are the most commonly searched types of Machine Learning Postdoc jobs in Massachusetts?

The most popular types of Machine Learning Postdoc jobs in Massachusetts are:

What are popular job titles related to Part Time Machine Learning Postdoc jobs in Massachusetts?

For Part Time Machine Learning Postdoc jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Part Time Machine Learning Postdoc jobs in Massachusetts look for?

The top searched job categories for Part Time Machine Learning Postdoc jobs in Massachusetts are:

Part Time Machine Learning Postdoc jobs near you
Infographic showing various Part Time Machine Learning Postdoc job openings in Massachusetts as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 22% Part Time, and 3% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution.

AI & Machine Learning Teaching Expert (Part-time)

On-site, Remote

TripleTen
See more jobs at TripleTenexternal

$152K/yr

Part-time

Re-posted 11 days ago

Job description

Description
TripleTen is an EdTech company that designs and runs tech career learning programs for the US and Latin American markets. We've been doing it for over five years, teaching complete beginners - people with no prior tech background - through cohort-based programs built on our own platform and curriculum, developed in partnership with Nebius AI. Our team is fully remote and globally distributed, and we serve a large, active student base across both regions.
We're looking for the person who brings an AI and Machine Learning curriculum to life for students: hosts the live sessions, reviews the work, runs the model and system review boards, and sets the technical bar for the people supporting alongside them. The curriculum is built by a team of senior authors.
This is a teaching and reviewing role. You'll be the senior technical presence students learn from week to week. You'll run live sessions and office hours, give real engineering feedback on student ML deliverables, and act as the escalation point for a team of supporting instructors who handle first-line questions. The best person for this is someone who has actually built and shipped AI systems in production, has opinions about what a sound ML system looks like, and can tell an experienced engineer why their approach is wrong.
Your audience: An experienced developer or engineer - SWE, data engineer, data analyst, DevOps/SRE, or quant - who wants to move into an adjacent AI/ML role (MLE, AI engineer, MLOps, data scientist) and carry their existing experience across, not start over.
Format: Live sessions, office hours, 1:1s, and workshops timed around US Eastern Time - mostly 2:00 PM to 9:00 PM ET. Estimated 10 to 15 hrs/week.
Please submit all resumes or CVs in English.
What you will do
  • Host live sessions focused on the design of ML systems: agentic architectures, orchestration, evaluation, and reliability of LLM-based systems.
  • Run group office hours, 1:1 sessions and tech mock interviews for students working through projects.
  • Review student projects against rubrics.
  • Set the technical standard for a team of supporting instructors who cover questions and first-line review, and act as their escalation point.

Requirements
  • 7+ years of professional ML engineering experience, currently working at senior level or above (Senior/Lead/Staff ML Engineer, AI Engineer, or ML/AI Systems Architect).
  • Has built and shipped AI or ML systems that ran in production in a real company, not just notebooks or side projects.
  • Depth across the AI engineering spine: agentic systems (L3, LangChain/CrewAI/ADK frameworks, orchestration, self-correction), agent reliability and guardrails, MCP; LLM evals (eval harness, LLM-as-judge, hallucination metrics), applied fine-tuning (SFT/LoRA); AI coding tools in the SDLC, LLM observability, A/B experiment design.
  • Can explain why a modeling or architecture decision was made, not just how it was implemented, and can diagnose and critique someone else's work live.
  • Strong technical communication: comfortable leading a live session and writing clear, specific review feedback.
  • Strong English C1+ - instruction and review are in English for a US-based audience.
  • Comfortable using AI tools in day-to-day technical work.

Preferred experience:
  • Has taught, mentored, or run technical sessions before: internal tech talks, onboarding, mentoring engineers, bootcamp or workshop instruction.
  • Production experience with agentic frameworks (LangChain, CrewAI, ADK) and MCP-based tool integrations.
  • Hands-on ownership of an eval or observability stack in production, not just usage.
  • Work experience at a recognizable company.
  • Familiarity with online education platforms or running programs.

What we can offer you
  • Fully remote work, with live sessions scheduled within US afternoon and evening hours.
  • A digital office: we use modern tools (Notion, Slack, Zoom) to keep collaboration smooth.
  • Professional trust and autonomy: no micromanaging.
  • A diverse, international, close-knit team excited to work with you!

Apply