Remote Machine Learning Scientist Jobs
Remote Machine Learning Scientist jobs are open across the U.S. at remote-first firms, distributed research teams, and technology-driven companies in sectors like software, healthcare, and finance. Employers hiring remote machine learning scientists right now include Artera, Rad AI, and A-Alpha Bio. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 14+ Remote Machine Learning Scientist jobs
About DDM Group
DDM Group is a digital media company with three properties: Atlanta Black Star, The Shadow League and Finurah. Over 14 years, DDM grew its audience to more than 20 million monthly users at peak entirely through organic distribution, without paid traffic. DDM has turned what it learned into a proprietary model of what captures an audience's attention and what moves people to change their behavior. We are now testing that model rigorously, and building it into an AI-powered service.
The role
You will own the evaluation of the model from raw data to verdict. You will build the dataset from 14 years of content and analytics (nearly 100,000 published articles on Atlanta Black Star alone, each with Google Analytics history), have AI models score the full archive, validate those scores against trained human raters on a sample, test whether those scores predict real audience behavior, and run live experiments on our properties. Your findings decide what we build and where we invest. We want an honest answer, including if the answer is no. If the model holds up, you will turn the evaluation pipeline into the core of the product: the scoring engine, the generator that proposes signals and plans, and the experiment and learning loop.
This is a remote contract role starting immediately. You will report to Neil Nelson, CEO, who owns the model, and work closely with our editorial team, whose producers serve as raters.
What you will do
Build the evaluation dataset: export story text and metadata from our WordPress sites, pull Google Analytics 4 data by traffic source, and recover older data from other sources where needed.
Design a balanced, representative sample, including stories that failed, not only the hits.
Run the scoring: set up blind rating, train and calibrate human raters with the editorial lead, measure how well raters agree, and write and validate the prompts for AI raters against human judgment.
Test the model: fit weights on one part of the data and validate them on data held back; compare alternative ways of combining scores; control for distribution effects such as platform algorithm changes and traffic source.
Test early-warning indicators on historical audience data.
Design, size and analyze live A/B tests on our properties.
Keep a clean, reproducible record of every dataset, decision, score, prediction and result.
Report findings plainly to the CEO, against success criteria agreed before the analysis begins.
About DDM Group
DDM Group is a digital media company with three properties: Atlanta Black Star, The Shadow League and Finurah. Over 14 years, DDM grew its audience to more than 20 million monthly users at peak entirely through organic distribution, without paid traffic. DDM has turned what it learned into a proprietary model of what captures an audience's attention and what moves people to change their behavior. We are now testing that model rigorously, and building it into an AI-powered service.
The role
You will own the evaluation of the model from raw data to verdict. You will build the dataset from 14 years of content and analytics (nearly 100,000 published articles on Atlanta Black Star alone, each with Google Analytics history), have AI models score the full archive, validate those scores against trained human raters on a sample, test whether those scores predict real audience behavior, and run live experiments on our properties. Your findings decide what we build and where we invest. We want an honest answer, including if the answer is no. If the model holds up, you will turn the evaluation pipeline into the core of the product: the scoring engine, the generator that proposes signals and plans, and the experiment and learning loop.
This is a remote contract role starting immediately. You will report to Neil Nelson, CEO, who owns the model, and work closely with our editorial team, whose producers serve as raters.
What you will do
Build the evaluation dataset: export story text and metadata from our WordPress sites, pull Google Analytics 4 data by traffic source, and recover older data from other sources where needed.
Design a balanced, representative sample, including stories that failed, not only the hits.
Run the scoring: set up blind rating, train and calibrate human raters with the editorial lead, measure how well raters agree, and write and validate the prompts for AI raters against human judgment.
Test the model: fit weights on one part of the data and validate them on data held back; compare alternative ways of combining scores; control for distribution effects such as platform algorithm changes and traffic source.
Test early-warning indicators on historical audience data.
Design, size and analyze live A/B tests on our properties.
Keep a clean, reproducible record of every dataset, decision, score, prediction and result.
Report findings plainly to the CEO, against success criteria agreed before the analysis begins.
See All 14 Remote Machine Learning Scientist Jobs
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Find JobsRemote Machine Learning Scientist Job Market
Who's Hiring
Top Industries Hiring
- Biotechnology & Pharmaceuticals
What Employers Look For
The qualifications that appear most often in remote machine learning scientist jobs.
- PhD or MS in computer science, statistics, or a closely related quantitative field
- Proficiency in Python with deep experience in PyTorch or TensorFlow
- Experience designing, training, and evaluating large-scale machine learning models
- Familiarity with cloud ML infrastructure such as AWS SageMaker, GCP Vertex AI, or Azure ML
- Strong publication record or demonstrated applied research output
- Experience with distributed training, model optimization, or MLOps pipelines
Tips for Your Remote Machine Learning Scientist Job Search
Apply early to remote roles that fit
Migrate Mate lists remote machine learning scientist openings from across the U.S. in one place, so you can find roles that match your skills and apply directly. Remote postings fill fast, so checking regularly and applying as soon as a strong fit appears gives you a real advantage.
Build a portfolio of reproducible experiments
Remote employers can't watch you work, so your code and notebooks do the talking. Host documented, reproducible experiments on GitHub that show your modeling decisions, not just final results. Clear commit histories and README files signal you can collaborate asynchronously on a distributed team.
Highlight async communication in your materials
Remote machine learning scientist roles require written communication that keeps distributed teammates aligned without meetings. Mention specific tools you've used, like GitHub pull requests, Confluence, or Weights and Biases experiment logs, and describe how your documentation practices kept cross-functional teams informed on model development progress.
Target remote-first companies in your research
Companies built as remote-first from the start have the infrastructure and culture to support distributed machine learning scientists effectively. Look for firms with fully distributed engineering and research teams, because those organizations hire remote scientists regularly and have onboarding processes designed for async work.
Remote Machine Learning Scientist Jobs: Frequently Asked Questions
How do I get a remote machine learning scientist job?
Focus on companies that operate distributed research teams, because those employers are already set up to manage remote scientists and actively hire them. Remote hiring managers screen hard for self-direction, clear written communication, and the ability to document experiments so teammates in different time zones can follow your reasoning. A public portfolio of reproducible work, strong Python and ML framework proficiency, and experience collaborating through async tools like GitHub and Confluence give candidates a clear edge.
Which companies hire remote machine learning scientists?
Companies hiring remote machine learning scientists right now include Artera, Rad AI, and A-Alpha Bio, based on current remote listings on Migrate Mate as of November 2026. Remote-first technology firms and distributed teams in software, healthcare, and financial services are among the most consistent hirers of machine learning scientists in fully remote roles.
Can you get a remote machine learning scientist job with no experience?
Yes, but remote entry-level machine learning scientist roles are harder to land because employers expect you to work independently from day one with minimal hand-holding. Smaller remote-first startups and research-oriented companies are more open to early-career candidates who can show original project work, published or open-source contributions, and strong written documentation skills that signal you'll function well on a distributed team.
Do you need a degree for remote machine learning scientist jobs?
Usually, but not always. Most remote machine learning scientist postings list a graduate degree as a preference, but remote employers increasingly weigh demonstrated skills, reproducible research, and real-world results alongside formal credentials. A strong portfolio of model development work, peer-reviewed contributions, or verifiable production deployments can offset the absence of an advanced degree for the right role.
Which industries hire the most remote machine learning scientists?
The sectors hiring the most remote machine learning scientists are Biotechnology & Pharmaceuticals, based on current remote listings on Migrate Mate as of November 2026. Those industries rely on distributed research and engineering teams that are structured to support scientists working fully remotely from the start.
See All 14 Remote Machine Learning Scientist Jobs
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