Member of Technical Staff

This is your opportunity to do the best work of your life. 

You will have a chance to shape the future of computing as part of a very small, passionate and highly technical team. A team, made up of quantum physicists, hardware engineers, and machine learning experts. 

Conductor Quantum is building the basic input output, and operating system for quantum computers. Our foundational software automates the calibration and tune-up of semiconductor spin qubits - turning raw silicon hardware into a ready-to-run quantum platform. By eliminating the biggest bottleneck in quantum computing (manual device configuration), we’re enabling a few, and eventually billions, of qubits to operate reliably at scale.

We are looking for individuals with high intelligence, high energy, and high integrity—driven by a hunger to change the world.

Role Overview: Member of Technical Staff

As a Member of Technical Staff, you will shape Conductor’s core offerings—software systems that analyze quantum device data in real-time, optimize qubit parameters, and seamlessly integrate with both on-premise and cloud infrastructures. You will architect, build, and maintain the next-generation control and calibration stack while collaborating closely with customers, physicists, and hardware engineers. This is a high-impact, high-ownership role, where you will define best practices, influence product strategy, and help lay the foundation for Conductor’s culture and growth.

Responsibilities and Skills

Customer Engagement & Product Strategy: Work directly with world-leading quantum companies and research labs to identify needs, shape product features and roadmaps, and demonstrate capabilities through demos, documentation, and interactive applications.

Data Analysis & Machine Learning: Develop Python pipelines to analyze large device datasets, build and deploy machine learning models for real-time qubit optimization, and utilize advanced techniques (e.g., Bayesian optimization, reinforcement learning) to solve calibration challenges.

Quantum Engineering & Simulation: Analyze data from semiconductor spin qubit devices to extract quantum features, performance metrics and identify optimization opportunities. Develop simulation models using advanced computational techniques and quantum physics to replicate device behavior. Design printed circuit boards (PCB), wire bond devices, and operate dilution refrigerators. Integrate with control electronics such as arbitrary-waveform generators, microwave sources and digital-to-analog converters.

Cloud Deployment & Scalable Infrastructure: Deploy machine learning models on cloud platforms (AWS/GCP/Azure), build back-end services for data collection and inference, and integrate with external systems for secure, reliable performance.