Quantum ML Engineer: Research-to-Production AI

Qubitera Ltd.; Cambridge; On-site; GBP 65,000 - 90,000; Full time

Job summary

Qubitera Ltd. is seeking a Machine Learning Engineer / AI Research Engineer to join a small core team in Cambridge, working at the intersection of modern machine learning and quantum computing.

The role is hands-on across research, design, coding, evaluation, and iteration. You'll design, train, and evaluate neural networks for quantum and classical directions, host and serve models (including LLMs), turn recent papers into code, and collaborate with quantum scientists and researchers at the

Qualifications

• Strong Python, with good software-engineering habits (Git, testing, reproducible experiments).
• Solid grounding in machine learning / deep-learning fundamentals — you can build, train, and debug neural networks from scratch in a modern framework (PyTorch, JAX, or similar).
• Demonstrable hands-on experience: research projects, publications, internships, open-source, or production work.
• Comfortable reading ML papers and reimplementing them.
• A fast learner who's happy with ambiguity and wants ownership.

Responsibilities

• You'll work across the full lifecycle — research, design, coding, evaluation, and iteration.
• You'll design, train, and evaluate neural networks for both directions.
• You'll help train, fine-tune, host, and serve models — including LLMs.
• Some of this you'll already know; parts you'll pick up on the job.
• You'll turn recent papers into working code, and working code into product.
• You'll collaborate closely with our quantum scientists, our CTO, and leading researchers at the University of Cambridge.
• You'll take real ownership of projects in a fast-moving, high-impact field.

Skills

Python

Neural networks

ML fundamentals

Reading ML papers

Ownership

Fast learner

LLMs

Tools

Git

PyTorch

JAX

Docker

Job description

Qubitera Ltd. is seeking a Machine Learning Engineer / AI Research Engineer to join a small core team in Cambridge, working at the intersection of modern machine learning and quantum computing.

The role is hands-on across research, design, coding, evaluation, and iteration. You'll design, train, and evaluate neural networks for quantum and classical directions, host and serve models (including LLMs), turn recent papers into code, and collaborate with quantum scientists and researchers at the