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Salary: CAD 140,000 - 190,000 / annual
Xanadu is building quantum computers that are useful and available globally. As an AI Specialist, you will drive applied AI initiatives by analyzing diverse R&D data and processes using state-of-the-art machine learning techniques including representation learning, generative modeling, and reinforcement learning. You will uncover hidden patterns in research across technical fields and contribute directly to developing internal R&D tool stacks that advance the first commercially viable quantum computer.
Your responsibilities include:
- Investigating and analyzing complex structured and unstructured data from internal R&D projects to identify key trends and insights
- Developing generalizable representation, reinforcement, and generative learning strategies for diverse research data
- Designing and implementing machine learning and optimization algorithms based on learned representations to solve specific R&D problems
- Developing and rigorously testing new ML algorithms and tool kits to improve R&D efficiency
- Collaborating closely with hardware engineers and scientists to create novel ML-driven solutions for complex research challenges
- Establishing and maintaining reproducible data analysis and modeling workflows
The AI team focuses on building and improving modeling, optimization, simulation, data processing, and design methodology for all internal research. You will work at the intersection of multiple technical disciplines with leading researchers, scientists, engineers, and software developers. The tech stack includes Python, Jupyter, JAX, GitHub, Docker, CI pipelines, and multiple cloud platforms.
REQUIREMENTS:
- BSc in Physics, Math, Computer Science, Engineering, or related field
- 4+ years of industry experience in deep learning/AI/ML, including at least one of: representation learning, reinforcement learning, geometric deep learning, computer vision, NLP, generative models, GFlowNet, control theory
- Strong Python proficiency and numerical/scientific ecosystem knowledge (JAX, NumPy, Pandas, XArray, PyTorch, CUDA, SciPy, scikit-learn, Ray, etc.)
- Deep mathematical understanding of machine learning and optimization
- Experience designing and building novel, generalizable representations of complex data structures with symmetries
- Hands-on experience with large-scale training of neural networks for RL, LLMs, diffusion models, or other generative modeling
- Experience with software development lifecycles (version control, code review, testing, CI/CD, logging, profiling, debugging, documentation)
- Comfortable with Linux shell, Docker, Git, and GitHub
- Enthusiasm for learning new technologies and scientific concepts with minimal supervision
- Solid communication and collaboration skills
- Strong self-driven analytical and problem-solving abilities
- Good knowledge of physics and linear algebra
PREFERRED:
- MSc/PhD in Computer Science, Engineering, Physics, Math, or related field
- Excellent knowledge in physics and linear algebra
- Familiarity with or curiosity towards quantum computing
- Experience in GFlowNet, geometric deep learning and equivariant models, ML on ultrafast embedded systems, or modeling/simulation of physical systems on HPC hardware
- Experience training commercial-grade LLMs
