Staff Machine Learning Research Developer
Listed on 2026-08-02
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IT/Tech
Machine Learning/ ML Engineer, Data Scientist, AI Business & Operations, AI Engineer (Applied/Software)
Staff Machine Learning Research Developer
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: .
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 alignonbest practices for machine learning system sand infrastructures, research, and products
Design and developsoftwareformachine learningmethodsusing annealing quantum computers
Research and develop machine learningmethodsexploiting optimization,sampling, and quantum simulationcapabilities of annealing quantum computers
Communicate with leadershiptoidentifyquantum machine learning opportunities
Consistently and comprehensivelydocumentresearch findings forpotentialpublicationsandforbuilding D-Wave’s internal knowledge base
Clearly and effectively communicate research findings and insightstoother D-Wave teams
Influence and guide thequantum machine learningroadmapby providing technical feedback to leadership
Lead and deliver goals on the quantum machine learning roadmap
Quickly digest research papers, reproduce results, and prototype and developnovelquantum machine learningmethods
What you'll bring
6+ years of professional experienceindevelopingdeeplearning models
An advanced degree (MS/PhD) in a STEM field, or added years of deep industry experience
Algorithmic reasoningshould be second nature (e.g.,data structuresand computational complexity)
Ability toquickly digestresearch papers and implement methods
Abreadth of knowledge ingenerativemachine 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,paralleltemperingand sequential Monte Carlo)
A solid understanding of Boltzmann Machines(i.e.,Ising models,Markovrandomfields,exponentialfamily distributions)
Familiarity with probabilistic graphical models
Familiarity with annealingand gate-basedquantum computers
Expertise with C++…
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