Machine Learning Engineer

We’re looking for a Machine Learning Research Engineer to join an early-stage quantum computing start-up developing full-stack quantum systems. This role sits at the intersection of advanced ML research and applied engineering, focusing on generative algorithms and hybrid quantum-classical models. You’ll work closely with clients and partners to show how ML and quantum technologies can solve real-world challenges. Responsibilities: * Design, implement, and evaluate new machine learning algorithms, particularly generative models (GANs, flow models, diffusion models) and hybrid quantum-classical neural networks. * Partner with clients to translate practical problems onto the company’s quantum hardware and deliver solutions that demonstrate value. * Expand and improve the company’s software platform with new algorithms, example applications, and research-driven features. * Support scientific innovation by publishing findings and helping safeguard intellectual property. Required Skills \& Experience: * Proven experience building and testing machine learning algorithms. * Hands-on experience with GANs, diffusion models, or flow-based generative models. * Strong programming skills in Python, PyTorch, and version control (Git). * Advanced degree (Master’s or PhD) in Computer Science, Physics, or a related technical field. Preferred Skills: * Experience working with specialized computing hardware (HPC, NPUs, ASICs, or quantum processors). * Multi-GPU training experience. * Publication record in ML or AI research. * Comfortable presenting and collaborating with clients or stakeholders. * Familiarity with quantum computing principles. Why Join: This role offers the chance to work on cutting-edge ML research applied to quantum hardware, delivering impactful solutions that move from concept to real-world implementation. The position provides hybrid flexibility in London and direct exposure to pioneering quantum technology.