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Added 4 hours ago
SM
RQ11718 – Software Developer – Intermediate
S M Software Solutions Inc
Toronto, ON
- Internship
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Added 4 hours ago
SM
RQ11718 – Software Developer – Intermediate
S M Software Solutions Inc
Toronto, ON
- Internship
We are seeking an experienced Intermediate Software Developer with strong hands-on expertise in Java Enterprise Edition (Java EE), n-tier enterprise application development, Spring…
Added 4 hours ago
SM
RQ11718 – Software Developer – Intermediate
S M Software Solutions Inc
Toronto, ON
- Internship
We are seeking an experienced Intermediate Software Developer with strong hands-on expertise in Java Enterprise Edition (Java EE), n-tier enterprise application development, Spring…
Added 4 hours ago
SJ
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Xanadu

Quantum Scientist - Finance

Toronto, ON, Canada

The base salary range is 100,000 - 140,000 CAD for intermediate and 150,000 - 180,000 CAD for senior. · Full-time

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Job details

Pay: The base salary range is 100,000 - 140,000 CAD for intermediate and 150,000 - 180,000 CAD for senior.
Job type: Full-time
Posting language: English
Posted: Sep 9, 2026

Original job description

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. What we are doing is extremely hard, the classic moon shot. 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 a quantum scientist, you will join a technical team of scientists dedicated to unlocking the real-world impact of fault-tolerant quantum computers. Your focus will be financial applications: quantum algorithms for partial differential equations (PDEs), quantum machine learning, and statistical estimation, and the question of where they can beat the classical methods banks and asset managers use today.

This is an algorithms-first role. Deep expertise in quantum algorithms is the core requirement, with specialization in partial differential equations, machine learning, and statistical estimation; familiarity with quantitative finance is what lets you aim those algorithms at problems that matter. This research is conducted directly alongside industry partners, requiring close collaboration with software, hardware, and business development teams across the company.

In more detail, you will focus deeply on two or more of the following areas:

Design quantum algorithms for the PDEs underlying derivative pricing and risk, including linear-systems and differential-equation solvers and the input/output bottlenecks that govern their usefulness.
Develop quantum machine learning and statistical estimation methods - amplitude estimation, Monte Carlo, and quantum approaches to regression, generative modelling, and time-series problems.
Identify high-value financial applications - pricing, risk and VaR, portfolio construction, calibration, fraud and anomaly detection - and establish credible advantage against strong classical baselines such as Monte Carlo, finite-difference and finite-element solvers, and modern deep learning.
Develop the core subroutines that quantum algorithms depend on: block encodings, Quantum Singular Value Transformations, data loading, and Hamiltonian simulation.
Radically improve algorithm efficiency by reducing qubit counts, non-Clifford gate complexity, and overall resource requirements.
Demonstrate feasibility and scalability through rigorous, constant-factor resource estimation.
Collaborate directly with financial-industry partners to translate their problems into well-posed quantum algorithmic questions and deliver honest assessments of what is achievable.
Work alongside compilation and quantum error correction (QEC) experts to compile these algorithms to fault-tolerant architectures.
Collaborate with PennyLane software developers to create state-of-the-art tools for quantum algorithms research.

Regardless of your specific focus areas, you will consistently:

Author high-quality scientific papers, technical reports, and comprehensive documentation.
Generate valuable intellectual property and actively support the filing of related patents.
Present your research findings to strategic partners and at premier conferences and events.

Basic qualifications and experience:

PhD in Physics, Computer Science, Mathematics, Engineering, Finance, or a related quantitative discipline - or equivalent practical experience.
Strong track record of research accomplishments in quantum computing, evidenced by publications, patents, or technical work.
Deep knowledge of fundamental concepts in quantum algorithms, such as Hamiltonian simulation, Trotter product formulas, quantum signal processing, linear combination of unitaries, amplitude amplification, quantum phase estimation, and quantum read-only memories.
Demonstrated specialization in quantum algorithms for differential equations and linear systems, and quantum machine learning.
Working knowledge of numerical PDE methods, stochastic processes, Monte Carlo estimation, statistical learning, and of the classical methods that serve as baselines.
Ability to reason quantitatively about the cost of an algorithm - not only asymptotic scaling, but where the leading constants and data-loading costs actually come from.
Capacity to thrive in an interdisciplinary team environment and drive independent research when required.
Excellent communication skills, with a proven ability to convey complex technical ideas to specialist and non-specialist audiences.
Strong self-management skills to balance individual project priorities, deadlines, and deliverables in a fast-paced environment.

Preferred qualifications and experience:

Previous experience applying quantum algorithms to finance, or experience in quantitative finance more broadly.
Experience performing constant-factor resource estimation for fault-tolerant quantum algorithms.
Familiarity with derivative pricing, risk modelling, or portfolio optimization, and with the data and latency constraints of production financial systems.
Practical experience with classical machine learning at scale (PyTorch, JAX) or with high-performance numerical PDE solvers.
Experience collaborating with industry or government partners on application benchmarking.
Strong software development and scientific programming skills in Python, preferably with a proven track record of contributing to open-source scientific libraries.
Solid understanding of quantum error correction and fault-tolerant architectures.
Knowledge of quantum compilation techniques.

This is for a new position. Your base salary will be determined based on your location, experience, and internal benchmarks. The base salary range is 100,000 - 140,000 CAD for intermediate and 150,000 - 180,000 CAD for senior. 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 recruiting@xanadu.ai.

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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More about this job

Responsibilities

The quantum scientist will design and develop quantum algorithms for financial applications such as derivative pricing, risk modeling, and machine learning. They will collaborate with cross-functional teams and industry partners to demonstrate the feasibility and scalability of these quantum solutions.

Requirements

Candidates must hold a PhD in a quantitative discipline and possess a strong research track record in quantum computing. Deep expertise in quantum algorithms, numerical methods, and the ability to communicate complex technical ideas to diverse audiences are essential.

Skills

Quantum algorithms
Partial differential equations
Quantum machine learning
Statistical estimation
Quantitative finance
Hamiltonian simulation
Monte Carlo
Python
PyTorch
JAX
Quantum error correction
Numerical PDE methods
Derivative pricing
Risk modeling
Portfolio optimization

Benefits

Equity
Benefits

Visa sponsorship

Not detected in the job text

Keywords

Quantum Computing
Quantum Algorithms
PDE Solvers
Quantum Machine Learning
Statistical Estimation
Quantitative Finance
Monte Carlo
Hamiltonian Simulation
Python
PyTorch
JAX
Derivative Pricing
Risk Management
Portfolio Construction
Quantum Error Correction
Fault-tolerant Architectures
PennyLane
Linear Systems
Stochastic Processes
Data Loading
Resource Estimation
Scientific Research
Intellectual Property
Algorithm Efficiency
Numerical Methods
Time-series Analysis
Generative Modelling
Regression
Quantum Signal Processing
Quantum Phase Estimation

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