Release Engineer

Salary Competitive

Equity To be negotiated

About QuantrolOx

QuantrolOx develops products that help quantum teams move from slow, manual workflows to fast, automated quantum R&D. The company focuses on two critical needs in the industry: automation tools for quantum hardware development and quantum workforce development.

Its products include Quantum EDGE, a measurement and automation platform for quantum hardware development, along with Quantum EDGE Academy for training future quantum engineers. QuantrolOx also offers VIDYAQAR, an integrated, open-architecture superconducting quantum system for education, research, testing, and benchmarking.

Together, Quantum EDGE Academy and VIDYAQAR create a practical training ladder for the next generation of quantum engineers.

Position Overview

Reporting to Technical Team Lead in Delft/Espoo you will have full ownership of the release management of our products, and end-to-end automation of the release and user management processes. You will be working closely with colleagues in our DevOps and QA teams building and continuously improving CI/CD pipelines.

Key Responsibilities

Plan and execute releasing of our products, maintaining an accurate record of installed versions, including SDK and instrument firmware.

Coordinate closely with QA team to ensure technical compatibility and testing coverage of installed combinations.
Optimise user management processes in collaboration with the product development team.
Automate all key aspects of the release and user management processes.
Coordinate with customers and internal teams to ensure smooth product updates.

Qualifications

A BSc or MSc in computer science or similar.
Experience in working with a major cloud platform and CI/CD pipelines are essential requirements.
Excellent communication skills with cultural awareness for effective global collaboration.
Familiarity with Google Cloud Platform, GitLab, Terraform, Auth0 and/or Moodle is a strong plus.

What We Offer

You will work with cutting edge software and cloud technologies that are aimed at world leaders in quantum computing.

Colleagues who are genuine leaders in quantum computing, software engineering and machine learning.
Flexible and innovation focused work environment.
Opportunity to shape the future of our release process from the ground up.

For more information or questions please contact us at careers@quantrolox.com

Perks and benefits

This job comes with several perks and benefits

Near public transit

Gym access

Maternity / paternity leave

Paid holiday

Remote work allowed

Work life balance

See all 8 benefits

Working at
QuantrolOx

See company profile

QuantrolOx is an Anglo-Finnish deep-tech startup, spun out of the University of Oxford in 2021 and now headquartered in Espoo, Finland. We build AI- and machine-learning-based control software that automatically tunes, stabilizes, and optimizes qubits, the fundamental building blocks of quantum computers. The problem: Unlike classical computers, which run reliably for years with no intervention, today's quantum computers require constant manual tuning by highly trained quantum physicists just to keep qubits calibrated. Qubits are extremely sensitive to noise and drift, and as systems scale from dozens of qubits to the hundreds of thousands or millions needed for useful computation, this manual tuning problem grows exponentially harder. As a result, quantum labs spend most of their time and expert talent maintaining hardware instead of running computations or advancing the science. Why it matters: This tuning bottleneck is one of the biggest practical barriers standing between today's experimental quantum computers and commercially useful machines. There simply aren't, and never will be, enough expert physicists to hand-tune millions of qubits one by one, so without automation the industry cannot scale. Our solution: QuantrolOx's software runs on classical hardware alongside the quantum system, continuously monitoring and adjusting many parameters in real time, on microsecond timescales. It is technology-agnostic and can be applied across different qubit platforms, though we have initially focused on solid-state qubits, where we've already demonstrated clear improvements in tuning speed and machine uptime. By automating this process, we free up scientists' time, increase the useful operating time of quantum computers, and remove a key bottleneck to scaling the entire field