Remote Machine Learning Research Engineer Jobs
Remote Machine Learning Research Engineer jobs are open across the U.S. in sectors like AI research, enterprise software, healthcare technology, and financial services, at both remote-first companies and large distributed engineering teams. Employers hiring remotely right now include Rad AI, Whatnot, and Bose. See the openings below and apply to the ones that match your experience.
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Showing 5 of 15+ Remote Machine Learning Research Engineer jobs
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Research Engineer — Agentic Audio ML Workflows
Description
At Bose Corporation, we believe sound is the most powerful force on earth — and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound.
Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation.
Job Description
Description
The goal of our team is to develop novel AI-powered audio processing algorithms. The twist is that our algorithms must run in real time, on physical devices. You will build agentic tools and automation that make our audio ML research dramatically faster and more reproducible. The focus is on orchestrating training, evaluation, experimentation, and reporting across many types of AI models, using on-premise and/or cloud GPU infrastructure.
Bose has a strong history of combining creative thinking with cutting-edge audio technology. We are looking for people passionate about machine learning and audio to help shape what comes next.
Responsibilities
- Design and implement agentic workflows that plan, launch, monitor, diagnose, and summarize audio ML experiments, with appropriate human oversight.
- Automate data preparation, model training, hyperparameter searches, benchmarking, regression testing, and result comparison across research projects.
- Build reliable tooling for on-premises GPU scheduling and utilization, experiment tracking, artifact management, and reproducible execution.
- Connect LLM-powered agents to scripts, repositories, datasets, evaluation suites, and compute resources through well-defined tools and safeguards.
- Partner with audio researchers to turn repetitive experiments into reusable workflows and clear dashboards or reports.
Education
Degree in computer science, machine learning, electrical engineering, or a related field, or equivalent practical experience.
Skills
- Strong software engineering and Python skills, with hands-on experience building LLM agents or agentic workflows that invoke tools and execute multi-step tasks.
- Comfortable tackling complex, open-ended problems where you have to experiment with and discard many ideas before finding the right solution.
- Experience with ML training and evaluation pipelines, PyTorch, experiment tracking, and automated testing.
- Practical experience operating on-premises Linux GPU machines, including CUDA environments, containers, job scheduling, and resource monitoring.
- Working knowledge of audio ML and DSP, including common datasets, audio metrics, and model development workflows.
- Experience with orchestration frameworks, distributed training, CI/CD, or MLOps is a plus.
- Ability to build reliable, observable systems and communicate effectively with research scientists.
At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Framingham, Massachusetts is: $165,400-$227,500.The hiring range for other Bose work locations may vary.

In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company—driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we’re creating what’s next—pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Let’s Make Waves.
Available in 16 locations See allSee all
Research Engineer — Agentic Audio ML Workflows
Description
At Bose Corporation, we believe sound is the most powerful force on earth — and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound.
Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation.
Job Description
Description
The goal of our team is to develop novel AI-powered audio processing algorithms. The twist is that our algorithms must run in real time, on physical devices. You will build agentic tools and automation that make our audio ML research dramatically faster and more reproducible. The focus is on orchestrating training, evaluation, experimentation, and reporting across many types of AI models, using on-premise and/or cloud GPU infrastructure.
Bose has a strong history of combining creative thinking with cutting-edge audio technology. We are looking for people passionate about machine learning and audio to help shape what comes next.
Responsibilities
- Design and implement agentic workflows that plan, launch, monitor, diagnose, and summarize audio ML experiments, with appropriate human oversight.
- Automate data preparation, model training, hyperparameter searches, benchmarking, regression testing, and result comparison across research projects.
- Build reliable tooling for on-premises GPU scheduling and utilization, experiment tracking, artifact management, and reproducible execution.
- Connect LLM-powered agents to scripts, repositories, datasets, evaluation suites, and compute resources through well-defined tools and safeguards.
- Partner with audio researchers to turn repetitive experiments into reusable workflows and clear dashboards or reports.
Education
Degree in computer science, machine learning, electrical engineering, or a related field, or equivalent practical experience.
Skills
- Strong software engineering and Python skills, with hands-on experience building LLM agents or agentic workflows that invoke tools and execute multi-step tasks.
- Comfortable tackling complex, open-ended problems where you have to experiment with and discard many ideas before finding the right solution.
- Experience with ML training and evaluation pipelines, PyTorch, experiment tracking, and automated testing.
- Practical experience operating on-premises Linux GPU machines, including CUDA environments, containers, job scheduling, and resource monitoring.
- Working knowledge of audio ML and DSP, including common datasets, audio metrics, and model development workflows.
- Experience with orchestration frameworks, distributed training, CI/CD, or MLOps is a plus.
- Ability to build reliable, observable systems and communicate effectively with research scientists.
At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Framingham, Massachusetts is: $165,400-$227,500.The hiring range for other Bose work locations may vary.

In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company—driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we’re creating what’s next—pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Let’s Make Waves.
See All 15 Remote Machine Learning Research Engineer Jobs
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Find JobsRemote Machine Learning Research Engineer Job Market
Who's Hiring
Top Industries Hiring
- Biotechnology & Pharmaceuticals
- Fintech
- Staffing & Recruiting
- Investment & Asset Management
What Employers Look For
The qualifications that appear most often in remote machine learning research engineer 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 large-scale machine learning experiments on distributed systems
- Peer-reviewed publications or preprints in relevant machine learning conferences or journals
- Hands-on experience with model training, evaluation, and deployment at production scale
- Familiarity with cloud computing platforms and GPU cluster management for research workloads
Tips for Your Remote Machine Learning Research Engineer Job Search
Apply early to remote roles that fit
Migrate Mate lists remote machine learning research engineer openings from across the U.S. in one place, so you can find roles that match your research focus and tech stack and apply directly without sifting through generalist boards.
Show your async research communication skills
Remote research teams run on written communication. Keep a public research blog, detailed README files, or Notion-style experiment logs that demonstrate you can explain complex model decisions clearly without a whiteboard or in-person meeting.
Build a reproducible remote portfolio
Host end-to-end ML projects on GitHub with clear environment setup, documented experiments tracked in MLflow or Weights and Biases, and a results summary any remote reviewer can run and verify without asking you questions first.
Prepare for async-first remote interviews
Many remote machine learning research engineer interviews include take-home research problems or asynchronous code reviews before any live call. Practice writing up your methodology and trade-off decisions clearly in writing, as if your reviewer is in a different time zone.
Remote Machine Learning Research Engineer Jobs: Frequently Asked Questions
How do I get a remote machine learning research engineer job?
Target companies that have built distributed research teams, including remote-first AI labs, enterprise software companies, and deep-tech startups where async collaboration is already the norm. Remote employers screen heavily for self-direction, strong written communication of research findings, and proficiency with MLOps tools and experiment-tracking platforms like MLflow or Weights and Biases. A public GitHub with reproducible research projects or published papers gives you a clear edge.
Which companies hire remote machine learning research engineers?
Remote machine learning research engineer roles are posted by Rad AI, Whatnot, and Bose and others right now, based on current remote listings on Migrate Mate as of November 2026. These tend to be remote-first AI companies, distributed enterprise tech teams, and research-driven organizations in sectors like healthcare AI, financial modeling, and autonomous systems.
Can you get a remote machine learning research engineer job with no experience?
Yes, but remote entry-level roles are competitive because you're expected to operate independently from day one without in-office mentorship. Focus on remote-first startups and AI research labs that hire junior researchers. A strong portfolio of end-to-end ML projects on GitHub, contributions to open-source model repositories, or a published preprint on arXiv can substitute meaningfully for professional experience when applying remotely.
Do you need a degree for remote machine learning research engineer jobs?
Not always. Many remote employers care more about demonstrated research ability than credentials, especially at smaller AI-focused companies and startups. A graduate degree in computer science, statistics, or a related field is common in research-heavy roles, but a strong project portfolio, open-source contributions, and evidence of shipping models into production carry real weight when employers can't assess you in person.
Which industries hire the most remote machine learning research engineers?
The sectors hiring the most remote machine learning research engineers are Biotechnology & Pharmaceuticals, Fintech, and Staffing & Recruiting, based on current remote listings on Migrate Mate as of November 2026. These industries rely on distributed research teams because the work is highly autonomous, deliverable-driven, and doesn't require physical presence to collaborate effectively.
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