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.

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