We are looking for a Quantum Developer and Researcher with a strong background in quantum algorithms to join our team. Prior experience in quantitative finance is not required. We value intellectual curiosity, strong analytical thinking, and openness to learning financial modeling concepts.

You will work closely with our quantitative analysts and research team on the development of quantum algorithms for derivative pricing, risk calculation, and interest rate modeling.

Key Responsibilities

• Collaborate with quantitative analysts to translate classical financial models into quantum-compatible computational frameworks.
• Design, implement, and optimize quantum algorithms for execution on current and near-term quantum hardware.
• Develop efficient quantum circuits with a strong focus on resource reduction and hardware constraints.
• Contribute to the design and implementation of a classical software library in Julia supporting quantum financial algorithms.
• Participate in research activities related to quantum computing applications in finance.

Requirements

• Strong academic background in quantum computing, algorithms, computer science, applied mathematics, or a related discipline (MSc or PhD preferred).
• Solid understanding of quantum algorithms, particularly: quantum arithmetic and reversible computation, Quantum Amplitude Estimation (QAE), and state preparation techniques.
• Strong programming skills in Python or Julia, with a willingness to work in Julia for production development.
• Ability to work with both research-grade prototypes and production-quality software.
• Strong analytical and problem-solving skills.

Nice to Have

• Experience with quantum SDKs such as Qiskit, PennyLane, Cirq, or Braket.
• Familiarity with fault-tolerant quantum computing concepts, quantum error correction and mitigation, and quantum resource estimation.
• Interest in computational finance, stochastic processes, or numerical methods.

What We Value

We are particularly interested in candidates with a deep understanding of core quantum algorithms and computational models, beyond variational or purely machine-learning-oriented approaches. Our work focuses on practical quantum algorithms for financial engineering and computational scalability on real quantum hardware.

About Us

At FinQbit, we're building the next generation of market risk management tools powered by quantum computing. Our mission is to deliver scalable, high-performance solutions for Monte Carlo, intensive problems in market risk, including Counterparty Credit Risk (CCR) and derivative pricing, especially in interest rate products.

Our tech stack is built in Julia, and we are passionate about innovation, precision, and pushing the boundaries of computational finance.