Remote Machine Learning Research Jobs
Remote Machine Learning Research jobs are open across the U.S. in AI research, applied science, and deep learning, with opportunities at remote-first labs, technology companies, and research-driven organizations ranging from early-career roles to principal researcher positions. Employers actively hiring remotely include Rad AI, Bose, and Cobalt. See the openings below and apply to the ones that match your experience.
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Showing 5 of 14+ Remote Machine Learning Research jobs
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.
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 14 Remote Machine Learning Research Jobs
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Find JobsRemote Machine Learning Research 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 jobs.
- PhD or MS in computer science, statistics, or a related quantitative field
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing and running controlled experiments on large-scale datasets
- Published or peer-reviewed research in a relevant machine learning subfield
- Ability to implement and evaluate state-of-the-art models from recent literature
- Strong written and verbal communication skills for presenting research findings internally
Tips for Your Remote Machine Learning Research Job Search
Apply early to remote roles that fit
Migrate Mate lists remote machine learning research openings from across the U.S. in one place. Search by role and apply directly to the positions that match your background without sorting through listings mixed with on-site roles.
Build a public research portfolio
Remote employers can't observe your process in person, so your visible output does the talking. Publish reproducible experiments, contribute to open-source machine learning projects, and document your methodology clearly so hiring teams can evaluate your thinking before the first conversation.
Sharpen your async written communication
Remote research teams run on written handoffs, design documents, and experiment logs. Practice writing concise, well-structured research updates and decision summaries. Strong async communication signals that you'll integrate into a distributed team without requiring constant check-ins.
Target remote-first organizations specifically
Companies built around distributed teams have established onboarding, tooling, and collaboration norms for remote researchers. Prioritize roles at remote-first AI labs and fully distributed product organizations, where remote work is the default rather than an exception made for a single hire.
Remote Machine Learning Research Jobs: Frequently Asked Questions
How do I get a remote machine learning research job?
Target companies with fully distributed research teams or remote-first cultures, since they have the infrastructure and norms to support independent research work. Remote employers screen for strong written communication, the ability to document experiments clearly, and self-directed project management. A public research portfolio, open-source contributions, or published work gives you a concrete edge over candidates with equivalent credentials but no visible output.
Which companies hire remote machine learning researchs?
Companies hiring remote machine learning researchs right now include Rad AI, Bose, and Cobalt, based on current remote listings on Migrate Mate as of November 2026. Remote-first AI labs, distributed product teams at technology companies, and research arms of enterprise software organizations are the most consistent sources of fully remote machine learning research roles.
Can you get a remote machine learning research job with no experience?
Yes, but remote entry-level research roles are harder to land because employers expect you to make progress independently without close supervision. Your best path is contributing to open-source machine learning projects, publishing reproducible experiments on public platforms, or completing research-track graduate coursework with visible outputs. Remote-first companies and smaller AI startups are more likely to hire entry-level candidates who demonstrate initiative through real, documented work.
Do you need a degree for remote machine learning research jobs?
Usually, but the weight placed on formal credentials varies by employer. Most research roles at established labs and larger companies expect a graduate degree in machine learning, computer science, or a related field. Remote-first startups and applied research teams are more willing to evaluate candidates on published work, GitHub contributions, and demonstrated research outcomes when those outputs are strong enough to stand on their own.
Which industries hire the most remote machine learning researchs?
Most remote machine learning research openings sit in Biotechnology & Pharmaceuticals, Fintech, and Staffing & Recruiting, per current remote listings on Migrate Mate as of November 2026. These sectors rely on distributed research teams because the work is computationally driven, documentation-heavy, and well-suited to asynchronous collaboration across time zones.
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