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Remote Edge Ai Machine Learning Jobs in Massachusetts

$152K/yr

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 ...

Machine Learning Scientist

Berlin, MA · On-site +1

  • Medical

  • Vision

About Nucs AI Nucs AI is revolutionizing cancer care through cutting-edge AI and medical imaging ... Autonomy and flexibility - Remote-first, flexible working. We hire great people and trust them to ...

Senior Machine Learning Engineer

Boston, MA · Remote

$140K - $190K/yr

... edge AI products that directly impact how new therapies reach patients. We're looking for an ... LI-Remote We value diversity and believe the unique contributions each of us brings drives our ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

... remote or hybrid options available). * The opportunity to work on life-changing AI technology that ... Join a team that combines cutting-edge innovation with a mission to save lives and improve health ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

... remote or hybrid options available). * The opportunity to work on life-changing AI technology that ... Join a team that combines cutting-edge innovation with a mission to save lives and improve health ...

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Machine Learning Engineer

Cambridge, MA · On-site +1

  • Medical

  • Retirement

Machine Learning Engineer - Computer Vision & Robotics Tycho.AI is redefining the future of ... If you want to work at the cutting edge of AI/ML and robotics with a company that's poised for ...

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Remote Edge Ai Machine Learning information

What is the difference between Remote Edge Ai Machine Learning vs Data Scientist?

AspectRemote Edge Ai Machine LearningData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with ML frameworksBachelor's or Master's in Statistics, CS, or related fields; strong analytical skills
Work EnvironmentRemote, often on edge devices or IoT systemsTypically office or remote, analyzing data in cloud or on-premises
Industry UsageAI development, IoT, autonomous systemsBusiness analytics, research, product development

Remote Edge Ai Machine Learning specialists focus on deploying ML models on edge devices, often requiring knowledge of embedded systems. Data Scientists analyze large datasets to extract insights, usually working in cloud environments. While both roles require strong ML fundamentals, their work environments and application areas differ significantly.

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

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What cities in Massachusetts are hiring for Remote Edge Ai Machine Learning jobs?

Cities in Massachusetts with the most Remote Edge Ai Machine Learning job openings:

AI & Machine Learning Teaching Expert (Part-time)

TripleTen

On-site, Remote

$152K/yr

Part-time

Posted 13 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!