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 Truveta, Cribl, and D-Wave. Find a role that fits below and apply directly.
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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 ML Research Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsRemote ML Research Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- 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 Truveta, Cribl, and D-Wave, per current remote listings on Migrate Mate as of August 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 Technology & Software and Staffing & Recruiting, per current remote listings on Migrate Mate as of August 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.
See All 9 Remote ML Research Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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