Remote ML Research Engineer Jobs
Remote ML Research Engineer jobs are open across the U.S. at remote-first firms and distributed teams in sectors including AI infrastructure, enterprise software, biotech, and defense. Employers hiring remote ml research engineers right now include Rad AI, Whatnot, and Bose. Find a role that fits below and apply directly.
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Showing 5 of 12+ Remote ML 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.
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Find JobsRemote ML Research Engineer Job Market
Who's Hiring
Top Industries Hiring
- Biotechnology & Pharmaceuticals
- Staffing & Recruiting
What Employers Look For
The qualifications that appear most often in remote ML research engineer jobs.
- Advanced degree in machine learning, computer science, or a closely related field
- Proficiency in Python and deep learning frameworks such as PyTorch or JAX
- Experience designing, training, and evaluating large-scale neural network models
- Publication record or demonstrated original research contributions in ML or AI
- Strong mathematical foundation in statistics, linear algebra, and optimization
- Experience with distributed training, cloud compute platforms, or MLOps tooling
Tips for Your Remote ML Research Engineer Job Search
Apply early to remote roles that fit
Migrate Mate lists remote ml research engineer openings from across the U.S. in one place, so you can find roles that match your background and apply directly without sorting through location-filtered noise. Early applications matter because competitive remote postings move fast.
Show your async research communication style
Remote ml research engineer teams rely on written documentation, shared experiment logs, and async code reviews. Include links to research writeups, Weights and Biases experiment summaries, or detailed pull request descriptions in your application materials to prove you can communicate research progress without synchronous standups.
Build a public portfolio of reproducible work
Remote hiring teams evaluate output, not proximity. Publish reproducible notebooks, model cards, and GitHub repositories that reflect the kinds of research problems you solve. Distributed teams can assess your technical depth and working style directly from your public artifacts before a single interview.
Prepare for distributed team interview formats
Remote ml research engineer interviews frequently include take-home research problems, async paper discussions, and multi-round video calls with teammates across time zones. Practice explaining architectural decisions and experimental tradeoffs clearly in writing, since many remote teams use written design reviews as a core evaluation step.
Remote ML Research Engineer Jobs: Frequently Asked Questions
How do I get a remote ml research engineer job?
Target remote-first AI labs, distributed product teams, and research-oriented tech companies, since these organizations are built for async collaboration and hire ml research engineers without geographic constraints. Remote employers screen heavily for self-direction, clear written communication, and the ability to document experiments and decisions asynchronously. A public portfolio of research work, published models, or open-source contributions gives candidates a concrete edge because remote hiring teams evaluate output over in-person presence.
Which companies hire remote ml research engineers?
Employers currently hiring remote ml research engineers include Rad AI, Whatnot, and Bose, per current remote listings on Migrate Mate as of November 2026. The mix typically includes remote-first AI labs, distributed enterprise software teams, and research divisions in biotech and defense that operate across multiple time zones.
Can you get a remote ml research engineer job with no experience?
Yes, but remote entry-level ml research engineer roles are harder to land because you must demonstrate independent work habits from day one without an office or in-person mentorship. Companies most likely to hire early-career candidates remotely include startups building ML tooling and academic research spinouts. A strong GitHub portfolio, reproducible research notebooks, and contributions to open-source ML projects can substitute meaningfully for formal work history.
Do you need a degree for remote ml research engineer jobs?
Not always, though most remote ml research engineer postings list a graduate degree in machine learning, computer science, or a related field as preferred. Remote employers weigh published research, demonstrable model-building skills, and hands-on results heavily alongside credentials. Candidates without a traditional degree who can show rigorous independent research, open-source contributions, or applied ML projects regularly compete successfully for these roles.
Which industries hire the most remote ml research engineers?
Most remote ml research engineer openings sit in Biotechnology & Pharmaceuticals and Staffing & Recruiting, per current remote listings on Migrate Mate as of November 2026. Those sectors rely on distributed research and engineering teams that make remote ml research engineer roles a structural part of how they build and iterate on models.
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