Staff Machine Learning Research Developer

Reposted 11 Days Ago
Be an Early Applicant
Burnaby, BC, CAN
In-Office
146K-219K Annually
Senior level
Information Technology • Software • Quantum Computing
The Role
Lead the design and development of software for quantum machine learning methods. Collaborate with researchers and communicate findings. Oversee best practices in machine learning systems and influence product offerings.
Summary Generated by Built In

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 (Burnaby)

Skills Required

  • 6-8+ years of professional experience in developing and deploying deep learning models
  • Familiarity with MLOps ecosystems
  • Advanced degree in STEM or deep industry experience
  • Expertise in delivering end-to-end software projects
  • Expertise in building extensible APIs and frameworks around PyTorch or similar
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The Company
Palo Alto, CA
199,202 Employees
Year Founded: 1999

What We Do

D-Wave is the leader in the development and delivery of quantum computing systems, software and services and is the world's first commercial supplier of quantum computers and the only company developing both annealing quantum computers and gate-model quantum computers. Our mission is to unlock the power of quantum computing for the world. We do this by delivering customer value with practical quantum applications for problems as diverse as logistics, artificial intelligence, materials sciences, drug discovery, scheduling, cybersecurity, fault detection, and financial modeling.

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