Lead AI/ML & MLOps Engineer executing projects from data foundations to model deployment. Collaborating with sales to drive AI/ML engagements for our clients.
About the role
- Staff Machine Learning Research Developer at D-Wave enabling quantum machine learning methods. Researching and developing software to enhance quantum computing capabilities for optimization and AI.
Responsibilities
- Help the team align on best practices for machine learning systems and infrastructures
- 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
- Document research findings for potential publications and internal knowledge base
- Communicate research findings and insights to other teams
- Influence and guide the quantum machine learning roadmap
- Lead and deliver goals on the quantum machine learning roadmap
- Digest research papers, reproduce results, and prototype and develop novel quantum machine learning methods
Requirements
- 6+ years of professional experience in developing deep learning models
- Advanced degree (MS/PhD) in a STEM field, or added years of deep industry experience
- Algorithmic reasoning
- Knowledge in generative machine learning paradigms (e.g., energy-based models, flow-based models, autoregressive models)
- Familiarity with Monte Carlo methods
- Solid understanding of Boltzmann Machines
- Familiarity with probabilistic graphical models
- 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
- Expertise in building extensible APIs and frameworks around PyTorch (or JAX and TensorFlow)
Benefits
- Company ownership
- Competitive pay
- Range of meaningful benefits
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