СШАAI Systems Engineer (NM)
1 мес. назад
75k–125k USD / годСША
quantum computingmachine learningpythondockerlinuxc++
Engineer working on AI infrastructure for quantum computing to automate calibration and operations of quantum hardware.
О компании
- High intelligence, high energy, and high integrity. People who are hungry to change the world and do not need to be told what to do next.
Обязанности
- As a Member of Technical Staff you will shape Conductor's core offerings: AI software that controls quantum hardware. From agentic quantum algorithm discovery and circuit generation code tools, all the way down to calibration and control of low-level qubit pulses. You will architect, build, and maintain the next-generation control and calibration stack. You will also build and maintain the first natural language interface for quantum computing, suitable for both human researchers and AI agents.
Условия
- Free healthcare, dental, and vision
- Work on the most important technical problem of our generation
Другое
- is building quantum superintelligence.
- Quantum superintelligence is an AI that uses quantum computers to surpass the capabilities of humanity's greatest minds. We are closer to that inflection point than most people realise. Frontier models are approaching general intelligence, and AI can already generate quantum circuits faster than humans can write them. The question is no longer whether quantum and AI converge; it is who builds the infrastructure to make that convergence reliable, scalable, and useful.
- That infrastructure starts with the hardware. The biggest bottleneck in quantum computing today is not qubit count; it is the manual configuration that keeps those qubits from being usable. Our software automates calibration and operations for spin and superconducting-qubit systems, turning raw cryogenic hardware into a stable, ready-to-run platform accessible through a simple chat interface. By solving that bottleneck, we are enabling thousands, and eventually billions, of qubits to operate reliably at scale.
- The result is a quantum computer as easy to use as ChatGPT. The first billion users are coming. The majority, we believe, will be AI agents.
- Today, AI generates production code faster and more reliably than most of the world's software engineers. AI is already generating quantum circuits. It just needs reliable hardware to run them on, well-calibrated qubits to utilise, and a feedback loop tight enough to discover new algorithms autonomously.
- The world's most capable AI models are being pointed at B2B SaaS. We are pointing ours at the frontier of science.
- 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.
- Develop Python pipelines to analyse large device datasets. Build and deploy machine learning models for real-time qubit optimisation. Apply advanced techniques such as Bayesian optimisation and reinforcement learning to solve calibration challenges.
- Analyse data from various quantum devices devices to extract quantum features, performance metrics, and optimisation opportunities. Develop simulation models using advanced computational techniques and quantum physics to replicate device behaviour. Integrate with control electronics such as arbitrary-waveform generators, microwave sources, and digital-to-analog converters.
- Build and maintain full-stack web applications. Deploy machine learning models on cloud platforms (AWS/GCP/Azure). Build back-end services for data collection, labelling, and inference. Integrate with external systems for secure, reliable performance. Own the natural language interface that makes our platform accessible to both humans and AI agents.
- Get deep on the current calibration stack, data pipelines, and customer integrations.
- Pair with the quantum engineers on at least one hardware-facing task, and see the lab realities your software serves.
- Design the system architecture for the AI-to-QPU integration layer, the interface between agents and quantum hardware that no one has built yet.
- Ship your first meaningful improvement to the calibration pipeline or the natural language interface.
- Identify the single highest leverage engineering improvement, and align the team on it.
- Have a clear architectural proposal for the next phase of the software stack
- Have at least one improvement in production that has moved a key metric. Time to a calibrated device, calibration success rate, and interface latency are examples of what we track.
- Have established the engineering practices the whole team builds on.
- Shape the product strategy and direction of the company.
- We are a small, passionate founding team of quantum physicists, hardware engineers, and machine learning experts. Our founders, Brandon and Joel, met each other at Oxford during their PhDs working on AI for quantum computing, where they saw first-hand that calibration and control is a core bottleneck to scaling quantum computers.
- This is your opportunity to do the best work of your life as part of that founding team.