$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 ...
New
$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 ...
New
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SD · Remote
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MO · Remote
$18 - $40/hr
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MO · Remote
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College Park, MD · Remote
$18 - $40/hr
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Machine Learning Tutor
College Park, MD · Remote
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Cambridge, MA · Remote
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Cambridge, MA · Remote
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Chandler, AZ · Remote
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VA · Remote
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Schaumburg, IL · Remote
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Schaumburg, IL · Remote
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Machine Learning Tutor
Miramar, FL · Remote
$18 - $40/hr
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Miramar, FL · Remote
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Erie, PA · Remote
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Erie, PA · Remote
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Machine Learning Tutor
PA · Remote
$18 - $40/hr
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Machine Learning Tutor
PA · Remote
$18 - $40/hr
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Des Plaines, IL · Remote
$18 - $40/hr
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Des Plaines, IL · Remote
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Sandy Springs, GA · Remote
$18 - $40/hr
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Sandy Springs, GA · Remote
$18 - $40/hr
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ID · Remote
$18 - $40/hr
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Machine Learning Tutor
ID · Remote
$18 - $40/hr
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Machine Learning Tutor
Conway, AR · Remote
$18 - $40/hr
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Machine Learning Tutor
Conway, AR · Remote
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Contract Machine Learning Teaching information
See salary details
$23K - $30K
11% of jobs
$30K - $36.9K
2% of jobs
$42.4K is the 25th percentile. Wages below this are outliers.
$36.9K - $43.9K
15% of jobs
The median wage is $49.9K / yr.
$43.9K - $50.8K
25% of jobs
$50.8K - $57.8K
16% of jobs
$59.9K is the 75th percentile. Wages above this are outliers.
$57.8K - $64.7K
21% of jobs
$64.7K - $71.7K
9% of jobs
$71.7K - $78.6K
0% of jobs
$78.6K - $85.6K
0% of jobs
$85.6K - $92.5K
0% of jobs
$92.5K - $99.5K
1% of jobs
$23K
$53.5K
$99.5K
How much do contract machine learning teaching jobs pay per year?
As of Aug 3, 2026, the average yearly pay for contract 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 cities are hiring for Contract Machine Learning Teaching jobs? Cities with the most Contract 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 Contract Machine Learning Teaching jobs? States with the most job openings for Contract Machine Learning Teaching jobs include:
$152K/yr
Part-time
Posted 3 days ago
New
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
Requirements
Preferred experience:
What we can offer you
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!