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Machine Learning Teaching Assistant Jobs (NOW HIRING)

TripleTen

$152K/yr

We're looking for the person who brings an AI and Machine Learning curriculum to life for students ... This is a teaching and reviewing role. You'll be the senior technical presence students learn from ...

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 ...

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 ...

Jobtailor

Machine Learning Engineer

California, MO · On-site

* Assist in designing, developing, and implementing machine learning models and algorithms * Assist in developing and optimizing machine learning models * Preprocess and analyze datasets to ensure ...

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 ... assistants, our internal stack for training models, and how to reason about performance. We're ...

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 ... assistants, our internal stack for training models, and how to reason about performance. We're ...

Bethany Learning Academy

Teaching Assistant

Orlando, FL · On-site

$23K/yr

You are passionate about learning and love working with children. With strong creative and ... A year of previous teaching assistant experience preferred * High-energy with a love of working ...

Dynamic Learning Academy

Teaching Assistant

Hammonton, NJ · On-site

$15.50 - $16.50/hr

As a Teaching Assistant, you will assist the classroom teacher with classroom duties and ... Your goal is to create a welcoming learning environment and provide students with the tools they ...

Dynamic Learning Academy

Teaching Assistant

Hammonton, NJ · On-site

$15.50 - $16.50/hr

As a Teaching Assistant, you will assist the classroom teacher with classroom duties and ... Your goal is to create a welcoming learning environment and provide students with the tools they ...

Dynamic Learning Academy

Teaching Assistant

Hammonton, NJ · On-site

$15.50 - $16.50/hr

As a Teaching Assistant, you will assist the classroom teacher with classroom duties and ... Your goal is to create a welcoming learning environment and provide students with the tools they ...

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Machine Learning Teaching Assistant information

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How much do machine learning teaching assistant jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for machine learning teaching assistant in the United States is $18.05, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $19.23 per hour, depending on experience, location, and employer.

What is a machine learning teaching assistant?

Machine Learning Teaching Assistants are individuals, often graduate students or knowledgeable undergraduates, who assist professors or instructors in teaching machine learning courses. Their responsibilities typically include helping students understand course material, grading assignments, holding office hours, and sometimes leading discussion or lab sessions. They act as a bridge between students and instructors, offering support for both theoretical concepts and practical implementation. By providing guidance and feedback, they help ensure students gain a solid understanding of machine learning principles and applications.

How does a machine learning teaching assistant typically collaborate with professors and students during a course?

As a Machine Learning Teaching Assistant, you will work closely with professors to develop and grade assignments, clarify course concepts, and facilitate discussions in lectures or lab sessions. You often serve as a bridge between students and faculty, providing guidance on programming tasks, troubleshooting code, and offering feedback on projects. Regular office hours and online forums are common venues for this support, making strong communication skills and a solid grasp of machine learning fundamentals essential. This collaborative environment helps you deepen your expertise while supporting student learning.

What are the key skills and qualifications needed to thrive as a machine learning teaching assistant, and why are they important?

To thrive as a Machine Learning Teaching Assistant, you need a solid foundation in machine learning concepts, programming (often Python), and relevant coursework or a degree in computer science or a related field. Familiarity with tools like Jupyter Notebooks, TensorFlow, PyTorch, and version control systems is commonly expected. Strong communication, patience, and organizational skills help you effectively support students and collaborate with instructors. These abilities ensure you can explain complex topics clearly, assist students efficiently, and contribute to a positive learning environment.

What cities are hiring for Machine Learning Teaching Assistant jobs?

Cities with the most Machine Learning Teaching Assistant 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 Machine Learning Teaching Assistant jobs?

States with the most job openings for Machine Learning Teaching Assistant jobs include:

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Machine Learning Teaching Assistant jobs near you
Infographic showing various Machine Learning Teaching Assistant job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $37,550 per year, or $18.1 per hour.

AI & Machine Learning Teaching Expert (Part-time)

On-site, Remote

TripleTen
See more jobs at TripleTenexternal

$152K/yr

Part-time

Re-posted 12 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