AI Specialist - AI For Research
$120k - $170k per yearXanadu
About Xanadu:
Xanadu’s mission is to build quantum computers that are useful and available to people everywhere.
At Xanadu, we are learners, innovators, researchers, collaborators and problem solvers. We are creating something that has never been built before. Few people in their life will be able to be a part of something like this, where if we are successful, the technologies we develop will solve some of the world’s most challenging problems, and literally change the world. And that is something to be excited about!
Your role and responsibilities:
As an AI Specialist at Xanadu, you will play a crucial role in integrating state of the art AI technologies into our R&D processes. This unique position allows you to contribute to the development of our internal automation stacks, aimed at advancing the first commercially viable quantum computer. The AI team’s focus is to accelerate and automate the discovery, optimization, and validation for our internal research. Situated at the intersection of multiple technical disciplines, you will have the opportunity to work with world leading researchers, scientists, engineers, and software developers. By infusing cutting-edge AI into internal R&D tooling, you have the chance to super-charge their research progress and even reshape how they work. You will:
- Build automated processes and feedback loops for executing complex research tasks at scale with Agentic AI.
- Develop Reinforcement Learning based environments for training reasoning models.
- Collaborate closely with researchers – theorists, experimentalists, engineers – to craft creative solutions for complex challenges.
- Ensure high-quality production code through automated tests, CI/CD pipelines, and code review processes.
At Xanadu, we primarily work with GitHub, Python, AWS, Postgres, Docker, Terraform, and Claude. Proficiency in these technologies is essential.
Required qualifications and experience:
- BSc. in Computer Science, Engineering, Physics, Math, or a related field.
- 4+ years of ML/Research Engineer experience developing models and/or AI tools in a scientific/engineering research environment.
- 2+ years of experience in at least one of these areas: Agentic Systems, Reinforcement Learning based feedback loops, or large-scale LLM training and deployment.
- Diverse experience with using and building AI agents, including context/harness engineering, knowledge retrieval, benchmarking performance, and multi-swarm Agent orchestration.
- Strong Software Engineering Skills.
- Good knowledge of physics and linear algebra.
Preferred qualifications and experience:
- PhD/MSc in Computer Science, Engineering, Physics, Math, or related field.
- Experience building domain specific agentic systems.
- Deep knowledge in physical sciences or math.
- Familiarity with quantum computing.
This is for an existing position. Your base salary will be determined based on your location, experience, and internal benchmarks. The base salary range is 120,000 - 170,000 CAD. You will also be eligible for equity and benefits.
Our values are important. They are fundamental and lay the foundation for culture at Xanadu. Learn more about our values here .
We are an equal opportunity employer and encourage candidates of all backgrounds to apply. We are committed to building an inclusive, safe, and equitable culture and fostering an environment where our employees feel included, valued, and heard. We are committed to meeting the needs of all individuals and support a barrier-free workplace. Should you require accommodations at any point during the recruitment process please contact Recruiting at View email address on jobs.jobcopilot.com .
Please be advised that we may use artificial intelligence (AI) tools to assist in the screening and assessment of applicants for this position. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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