Remote Machine Learning Researcher Jobs
Remote Machine Learning Researcher jobs are in active demand across the U.S., with remote-first firms, distributed AI teams, and research-driven organizations in technology, finance, and healthcare hiring researchers who can work independently from anywhere. Employers hiring remotely right now include Cobalt, Xcerra, and Truveta. Find a role that fits below and apply directly.
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Showing 4 of 12+ Remote Machine Learning Researcher jobs
Job Type: Flexible Contract (Remote)
Job Summary: We are hiring PhD-level Machine Learning Researchers for a contract project that tests whether frontier AI models can handle real research-grade machine learning work. You will create hard command line tasks from your field that a leading AI model cannot solve, then review where and why it fails.
What you will do
- Create command line tasks based on real machine learning research problems.
- Reproduce a result from a recent paper, including the training recipe, data processing and evaluation.
- Find the flaw in an experimental setup, such as a train-test leak, an unfair baseline, a wrong metric or a seed-dependent result.
- Diagnose a failing training run, such as diverging loss, vanishing gradients or silent numerical errors.
- Implement a loss function, optimizer, attention variant or sampling method from its mathematical description.
- Fix or extend an evaluation harness so that a benchmark comparison is valid.
- Build each task’s environment, including the code, data and dependencies, and write a reference solution.
- Write automated tests that check whether a solution is correct, with consistent results on every run (fixed seeds, tolerance-based checks).
- Run your task against a leading AI model, review its attempt, and adjust the task until the model fails because the problem is truly hard, not because the instructions are unclear.
Who we are looking for
- A PhD in machine learning, computer science, statistics, applied mathematics, engineering or another STEM field. PhD candidates and students are welcome to apply.
- Hands-on research or industry experience in machine learning. Ten or more years of experience in machine learning, systems or security is ideal.
- At least one publication, academic or professional.
- Strong experience with PyTorch, JAX or TensorFlow, including debugging real training runs.
- Comfort with Python, the Linux command line, Docker and Git.
- Experience with experimental design, benchmarking or testing AI systems is a plus.
- Experience with LLM training, evaluation or reinforcement learning is a plus.
- Peer review experience, or experience building technical tests or assessments, is an advantage.
- Able to work independently in a remote setting and explain technical findings clearly.
Why Cobalt AI
- Advance frontier AI where it counts. Apply your expertise to the data frontier labs cannot get any other way, where your reasoning directly shapes how the next generation of models solves technical problems.
- Grow professionally. Expand your influence through evaluation projects, advisory roles and research collaborations, while deepening your understanding of how frontier models are trained and assessed.
- Work with a top-tier network. Collaborate with researchers and engineers from leading institutions and labs on high-impact, flexible work.
- Set your own schedule. Flexible 10 to 40 hour weeks that fit around your current role and your life.
- Competitive pay. Paid per accepted task, with higher rates for consistently strong work.
Education:
- Doctorate (Required)
Work Location: Remote
Job Type: Flexible Contract (Remote)
Job Summary: We are hiring PhD-level Machine Learning Researchers for a contract project that tests whether frontier AI models can handle real research-grade machine learning work. You will create hard command line tasks from your field that a leading AI model cannot solve, then review where and why it fails.
What you will do
- Create command line tasks based on real machine learning research problems.
- Reproduce a result from a recent paper, including the training recipe, data processing and evaluation.
- Find the flaw in an experimental setup, such as a train-test leak, an unfair baseline, a wrong metric or a seed-dependent result.
- Diagnose a failing training run, such as diverging loss, vanishing gradients or silent numerical errors.
- Implement a loss function, optimizer, attention variant or sampling method from its mathematical description.
- Fix or extend an evaluation harness so that a benchmark comparison is valid.
- Build each task’s environment, including the code, data and dependencies, and write a reference solution.
- Write automated tests that check whether a solution is correct, with consistent results on every run (fixed seeds, tolerance-based checks).
- Run your task against a leading AI model, review its attempt, and adjust the task until the model fails because the problem is truly hard, not because the instructions are unclear.
Who we are looking for
- A PhD in machine learning, computer science, statistics, applied mathematics, engineering or another STEM field. PhD candidates and students are welcome to apply.
- Hands-on research or industry experience in machine learning. Ten or more years of experience in machine learning, systems or security is ideal.
- At least one publication, academic or professional.
- Strong experience with PyTorch, JAX or TensorFlow, including debugging real training runs.
- Comfort with Python, the Linux command line, Docker and Git.
- Experience with experimental design, benchmarking or testing AI systems is a plus.
- Experience with LLM training, evaluation or reinforcement learning is a plus.
- Peer review experience, or experience building technical tests or assessments, is an advantage.
- Able to work independently in a remote setting and explain technical findings clearly.
Why Cobalt AI
- Advance frontier AI where it counts. Apply your expertise to the data frontier labs cannot get any other way, where your reasoning directly shapes how the next generation of models solves technical problems.
- Grow professionally. Expand your influence through evaluation projects, advisory roles and research collaborations, while deepening your understanding of how frontier models are trained and assessed.
- Work with a top-tier network. Collaborate with researchers and engineers from leading institutions and labs on high-impact, flexible work.
- Set your own schedule. Flexible 10 to 40 hour weeks that fit around your current role and your life.
- Competitive pay. Paid per accepted task, with higher rates for consistently strong work.
Education:
- Doctorate (Required)
Work Location: Remote
See All 12 Remote Machine Learning Researcher Jobs
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Find JobsRemote Machine Learning Researcher Job Market
Who's Hiring
Top Industries Hiring
- Fintech
- Investment & Asset Management
What Employers Look For
The qualifications that appear most often in remote machine learning researcher jobs.
- PhD or Master's degree in machine learning, computer science, or a closely related field
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing and running experiments with large-scale datasets
- Strong publication record or demonstrated original research contributions
- Familiarity with distributed training, model optimization, and evaluation pipelines
- Ability to communicate research findings clearly to both technical and non-technical audiences
Tips for Your Remote Machine Learning Researcher Job Search
Apply early to remote roles that fit
Migrate Mate lists remote machine learning researcher openings from across the U.S. in one place, so you can find roles that match your research focus and apply directly without sifting through non-remote or unrelated postings.
Show your research output publicly
Remote employers can't observe your work in person, so your GitHub repositories, arXiv preprints, or Kaggle notebooks do that work for you. Link directly to documented projects that show your methodology, not just your code.
Write your way into async-first teams
Remote machine learning researcher teams run on written communication. Practice writing clear, concise experiment summaries and async research updates. Sharing a sample research log or annotated notebook in your application signals you can collaborate without meetings.
Target remote-first companies with AI research teams
Remote-first technology companies and AI-focused startups have built the infrastructure for distributed research work. Focusing your search on organizations that were remote before it was common means you'll join teams with mature async workflows rather than improvised ones.
Remote Machine Learning Researcher Jobs: Frequently Asked Questions
How do I get a remote machine learning researcher job?
Remote machine learning researcher roles go to candidates who can demonstrate deep technical ability and the discipline to drive research independently without in-person oversight. Remote employers screen heavily for strong written communication, since async collaboration replaces most meetings. Candidates with published work, open-source contributions, or documented research projects stand out because they show results without requiring in-person validation.
Which companies hire remote machine learning researchers?
Employers currently hiring remote machine learning researchers include Cobalt, Xcerra, and Truveta, per current remote listings on Migrate Mate as of November 2026. Remote-first technology companies, AI-focused startups, and distributed research teams in finance and healthcare are among the most consistent hirers of this role.
Can you get a remote machine learning researcher job with no experience?
Yes, but remote entry-level machine learning researcher roles are harder to land because employers expect you to work independently from day one with minimal hand-holding. Smaller remote-first companies and AI startups are most open to entry-level candidates. A portfolio of real research projects, Kaggle competition results, or a published paper can substitute for formal experience when applying remotely.
Do you need a degree for remote machine learning researcher jobs?
Usually, but a master's or PhD is not always required if you can demonstrate equivalent depth through published research, documented projects, or strong open-source contributions. Remote employers for this role weigh demonstrated research output and proficiency in frameworks like PyTorch or JAX alongside formal credentials, especially at smaller companies where results matter more than credentials.
Which industries hire the most remote machine learning researchers?
Most remote machine learning researcher openings sit in Fintech and Investment & Asset Management, per current remote listings on Migrate Mate as of November 2026. These sectors rely on distributed research teams that can operate fully asynchronously, making remote machine learning researcher roles a natural fit for their hiring models.
See All 12 Remote Machine Learning Researcher Jobs
Find roles that match your experience and apply in just a few clicks.
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