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 Cribl, D-Wave, and Deepgram. See the openings below and apply to the ones that match your experience.
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Showing 5 of 9+ Remote Machine Learning Research jobs
D-Wave (NYSE: QBTS), D-Wave is a leader in the development and delivery of quantum computing systems, software, and services. We are the world’s first commercial supplier of quantum computers, and the only company building both annealing and gate-model quantum computers. Our mission is to help customers realize the value of quantum, today. Our quantum computers — the world’s largest — feature QPUs with sub-second response times and can be deployed on-premises or accessed through our quantum cloud service, which offers 99.9% availability and uptime. More than 100 organizations trust D-Wave with their toughest computational challenges. With over 200 million problems submitted to our quantum systems to date, our customers apply our technology to address use cases spanning optimization, artificial intelligence, research and more. Learn more about realizing the value of quantum computing today and how we’re shaping the quantum-driven industrial and societal advancements of tomorrow: www.dwavequantum.com.
You can read more about our company and our innovations in the pages of The Wall Street Journal, Time Magazine, Fast Company, MIT Technology Review, Forbes, Inc. Magazine, Wired and across many whitepapers.
At D-Wave, we’re helping customers realize the value of quantum computing today and are shaping the quantum-driven industrial and societal advancements of tomorrow.
About the role
D-Wave is seeking a Staff Machine Learning Research Developer to work alongside our researchers, solutions architects, and software developers specializing in various domains (e.g., combinatorial optimization, graph theory, and quantum physics).
As a senior member of the Machine Learning Development team, you will have the opportunity to influence our product offerings. You will lead the architectural design and development of our software to enable researchers and solutions architects to rapidly prototype and experiment with quantum machine learning methods. In parallel, you will research and develop machine learning methods exploiting the optimization, sampling, and quantum simulation capabilities of quantum computers.
We are looking for intrinsically motivated individuals who want to make technological and tangible impacts at the intersection of quantum computing and machine learning.
What you'll do
- Help the team align on best practices for machine learning systems and infrastructures, research, and products
- Design and develop software for machine learning methods using annealing quantum computers
- Research and develop machine learning methods exploiting optimization, sampling, and quantum simulation capabilities of annealing quantum computers
- Communicate with leadership to identify quantum machine learning opportunities
- Consistently and comprehensively document research findings for potential publications and for building D-Wave’s internal knowledge base
- Clearly and effectively communicate research findings and insights to other D-Wave teams
- Influence and guide the quantum machine learning roadmap by providing technical feedback to leadership
- Lead and deliver goals on the quantum machine learning roadmap
- Quickly digest research papers, reproduce results, and prototype and develop novel quantum machine learning methods
What you'll bring
- 6+ years of professional experience in developing deep learning models
- An advanced degree (MS/PhD) in a STEM field, or added years of deep industry experience
- Algorithmic reasoning should be second nature (e.g., data structures and computational complexity)
- Ability to quickly digest research papers and implement methods
- A breadth of knowledge in generative machine learning paradigms (e.g., energy-based models, flow-based models, autoregressive models) complemented by a depth of knowledge in several subdomains
- Strong problem-solving, communication, and collaboration skills
Nice to have
- Familiarity with Monte Carlo methods (e.g., Metropolis-Hastings, Gibbs, parallel tempering and sequential Monte Carlo)
- A solid understanding of Boltzmann Machines (i.e., Ising models, Markov random fields, exponential family distributions)
- Familiarity with probabilistic graphical models
- Familiarity with annealing and gate-based quantum computers
- Expertise with C++ or other low-level programming languages
- Contributions to open-source software
- Familiarity with MLOps ecosystems (e.g., Kubeflow, VertexAI, Airflow) Experience in delivering end-to-end software projects
- -from architect to deployment
- Expertise in building extensible APIs and frameworks around PyTorch (or, e.g., JAX and TensorFlow)
A D-Waver's DNA
- We look at the future and say “why not”; we see possibilities where others see problems or routines. We show the way ahead and are committed to achieving ambitious goals.
- We practice straight talk and listen generously to each other with empathy. We value different opinions and points of views. We ensure that we connect outside as well as inside to learn from others and inspire each other.
- We hold ourselves accountable for delivering results. We make decisions & take responsibility so that we can act & support each other.
- As leaders we motivate & engage our teams to undertake beyond what they originally thought possible, by developing our teams & creating the conditions for people to grow and empower themselves through enabling & coaching.
Our Compensation Philosophy is Simple but Powerful:
We believe providing D-Wavers with company ownership, competitive pay, and a range of meaningful benefits is the start of creating a culture where people want to give the best they’ve got — not because they’re simply making money, but because they’ve fallen in love with our vision, mission, values, and team.
During the interview process, your Recruiter will review our total rewards (base, equity, bonus, perks, benefit, culture) offerings. The final offer is determined by your proficiencies within this level.
Inclusion:
We celebrate diverse perspectives to drive innovation in our pursuit. Our employees range from distinguished domain experts with decades of experience in their respective fields, to bright and motivated graduates eager to make their mark. Our diverse and innovative team will make you feel appreciated, supported and empower your career growth at D-Wave.
The Fine Print:
No 3rd party candidates will be accepted
It is D-Wave Systems Inc. policy to provide equal employment opportunity (EEO) to all persons regardless of race, color, religion, sex, national origin, age, sexual orientation, gender identity, genetic information, physical or mental disability, protected veteran status, or any other characteristic protected by federal, state/provincial, local law.
The base pay range for this role is:
$146,182 - $219,273 CAD per year
$167,000 - $230,000 USD per year
D-Wave (NYSE: QBTS), D-Wave is a leader in the development and delivery of quantum computing systems, software, and services. We are the world’s first commercial supplier of quantum computers, and the only company building both annealing and gate-model quantum computers. Our mission is to help customers realize the value of quantum, today. Our quantum computers — the world’s largest — feature QPUs with sub-second response times and can be deployed on-premises or accessed through our quantum cloud service, which offers 99.9% availability and uptime. More than 100 organizations trust D-Wave with their toughest computational challenges. With over 200 million problems submitted to our quantum systems to date, our customers apply our technology to address use cases spanning optimization, artificial intelligence, research and more. Learn more about realizing the value of quantum computing today and how we’re shaping the quantum-driven industrial and societal advancements of tomorrow: www.dwavequantum.com.
You can read more about our company and our innovations in the pages of The Wall Street Journal, Time Magazine, Fast Company, MIT Technology Review, Forbes, Inc. Magazine, Wired and across many whitepapers.
At D-Wave, we’re helping customers realize the value of quantum computing today and are shaping the quantum-driven industrial and societal advancements of tomorrow.
About the role
D-Wave is seeking a Staff Machine Learning Research Developer to work alongside our researchers, solutions architects, and software developers specializing in various domains (e.g., combinatorial optimization, graph theory, and quantum physics).
As a senior member of the Machine Learning Development team, you will have the opportunity to influence our product offerings. You will lead the architectural design and development of our software to enable researchers and solutions architects to rapidly prototype and experiment with quantum machine learning methods. In parallel, you will research and develop machine learning methods exploiting the optimization, sampling, and quantum simulation capabilities of quantum computers.
We are looking for intrinsically motivated individuals who want to make technological and tangible impacts at the intersection of quantum computing and machine learning.
What you'll do
- Help the team align on best practices for machine learning systems and infrastructures, research, and products
- Design and develop software for machine learning methods using annealing quantum computers
- Research and develop machine learning methods exploiting optimization, sampling, and quantum simulation capabilities of annealing quantum computers
- Communicate with leadership to identify quantum machine learning opportunities
- Consistently and comprehensively document research findings for potential publications and for building D-Wave’s internal knowledge base
- Clearly and effectively communicate research findings and insights to other D-Wave teams
- Influence and guide the quantum machine learning roadmap by providing technical feedback to leadership
- Lead and deliver goals on the quantum machine learning roadmap
- Quickly digest research papers, reproduce results, and prototype and develop novel quantum machine learning methods
What you'll bring
- 6+ years of professional experience in developing deep learning models
- An advanced degree (MS/PhD) in a STEM field, or added years of deep industry experience
- Algorithmic reasoning should be second nature (e.g., data structures and computational complexity)
- Ability to quickly digest research papers and implement methods
- A breadth of knowledge in generative machine learning paradigms (e.g., energy-based models, flow-based models, autoregressive models) complemented by a depth of knowledge in several subdomains
- Strong problem-solving, communication, and collaboration skills
Nice to have
- Familiarity with Monte Carlo methods (e.g., Metropolis-Hastings, Gibbs, parallel tempering and sequential Monte Carlo)
- A solid understanding of Boltzmann Machines (i.e., Ising models, Markov random fields, exponential family distributions)
- Familiarity with probabilistic graphical models
- Familiarity with annealing and gate-based quantum computers
- Expertise with C++ or other low-level programming languages
- Contributions to open-source software
- Familiarity with MLOps ecosystems (e.g., Kubeflow, VertexAI, Airflow) Experience in delivering end-to-end software projects
- -from architect to deployment
- Expertise in building extensible APIs and frameworks around PyTorch (or, e.g., JAX and TensorFlow)
A D-Waver's DNA
- We look at the future and say “why not”; we see possibilities where others see problems or routines. We show the way ahead and are committed to achieving ambitious goals.
- We practice straight talk and listen generously to each other with empathy. We value different opinions and points of views. We ensure that we connect outside as well as inside to learn from others and inspire each other.
- We hold ourselves accountable for delivering results. We make decisions & take responsibility so that we can act & support each other.
- As leaders we motivate & engage our teams to undertake beyond what they originally thought possible, by developing our teams & creating the conditions for people to grow and empower themselves through enabling & coaching.
Our Compensation Philosophy is Simple but Powerful:
We believe providing D-Wavers with company ownership, competitive pay, and a range of meaningful benefits is the start of creating a culture where people want to give the best they’ve got — not because they’re simply making money, but because they’ve fallen in love with our vision, mission, values, and team.
During the interview process, your Recruiter will review our total rewards (base, equity, bonus, perks, benefit, culture) offerings. The final offer is determined by your proficiencies within this level.
Inclusion:
We celebrate diverse perspectives to drive innovation in our pursuit. Our employees range from distinguished domain experts with decades of experience in their respective fields, to bright and motivated graduates eager to make their mark. Our diverse and innovative team will make you feel appreciated, supported and empower your career growth at D-Wave.
The Fine Print:
No 3rd party candidates will be accepted
It is D-Wave Systems Inc. policy to provide equal employment opportunity (EEO) to all persons regardless of race, color, religion, sex, national origin, age, sexual orientation, gender identity, genetic information, physical or mental disability, protected veteran status, or any other characteristic protected by federal, state/provincial, local law.
The base pay range for this role is:
$146,182 - $219,273 CAD per year
$167,000 - $230,000 USD per year
See All 9 Remote Machine Learning Research Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsRemote Machine Learning Research Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- 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 Cribl, D-Wave, and Deepgram, based on current remote listings on Migrate Mate as of August 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 Technology & Software, Fintech, and Staffing & Recruiting, per current remote listings on Migrate Mate as of August 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.
See All 9 Remote Machine Learning Research Jobs
Find roles that match your experience and apply in just a few clicks.
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