Machine Learning Engineer

** Instructions on how to apply are at the bottom of the page **

About auryx

auryx is on a mission to create the world’s best foundation model for turning sound into health insights, transforming preventative health monitoring. We are a small, ambitious team combining cutting-edge research and world-class expertise in biomedical engineering, audio signal processing, and AI to unlock new ways of measuring human health.

Our technology currently uses machine learning to turn regular existing earbuds into health and fitness sensors, tracking heart rate, HRV, respiration, and advanced cardiovascular parameters, all through devices people already own. We have built early models for our core technology and we are now looking for a machine learning engineer to build and deploy on-device ML models for health and biosignal monitoring on earbuds, helping to take our technology from proof of concept to a world-class product.

The role

As a machine learning engineer at auryx, you will focus on building and optimising ML models for on-device health monitoring on earbuds. Most of your work will be on developing models that run efficiently on constrained devices, including experimenting with architectures, applying optimisation techniques, and implementing solutions for real-world deployment. You may also contribute to earlier-stage model development, helping refine and extend research prototypes into production-ready systems.

As an early employee, you will have significant potential to bring ownership and direction to our technical work while contributing across the breadth of startup activities. Beyond core ML development, you might find yourself contributing to product decisions, diving into hardware integration challenges, supporting data collection and validation efforts, or helping shape our approach to health feature development and user testing.

You will work closely with the CTO on a day-to-day basis, collaborating on the design, development and deployment of our ML system. The position offers the full spectrum of early-stage startup experience — from prototyping and technical problem-solving to strategic planning and cross-team collaboration, giving you exposure to both complex technical challenges and the decision-making that defines our product roadmap and company trajectory.

What we are looking for

• Ph.D. or Master’s degree in Computer Science, Machine Learning, Information Engineering, Biomedical Engineering, or a related field.
• Strong background in deep learning (PyTorch/TensorFlow) and Python development.
• Experience with on-device ML (TinyML), including frameworks such as TensorFlow Lite, ExecuTorch, TVM, or equivalent.
• Solid understanding of model optimisation techniques (quantisation, pruning, compression) to make models efficient on constrained devices.
• Proven ability to write clean, maintainable, and well-tested code in a collaborative environment.
• Curiosity, willingness to learn, and flexibility to adapt and grow in a fast-moving, uncertain startup environment.
• Ability to take ownership and independently drive on-device ML projects, while collaborating with the team to deliver high-quality outcomes.

Nice to have

• Experience in processing time series data such as audio, biosignals, or other sensor modalities.
• Familiarity with biomedical signal processing and signal processing fundamentals.
• Experience writing production-level code (backend, APIs, or embedded integration).
• Early-stage startup experience.
• Experience with medical device regulations (like FDA, CE marking) is advantageous, but not necessary.

Why join us?

• Competitive salary.
• Equity options giving you a stake in the company’s success.
• Be an integral part of a pioneering, mission-driven team.
• Significant ownership over your projects – we value growth and initiative, and always recognise your contributions.
• Flexible working.
• Generous holiday policy – 25 days + bank holidays + 1 personal life event day.

Location

Hybrid in Cambridge, UK (preferred)/remote

How to Apply

Send your application to Kayla (CTO) at kayla@auryx.ai with:

• Your CV and LinkedIn profile.
• Links to any relevant work or projects you've been a part of.
• A brief note on why you are a good fit to work in AI for health and physiological sensing (250 words max).

Our selection process includes multiple technical and culture interviews with members of the founding team, and a final interview, where we walk through all aspects of the role.

auryx is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

If that sounds like a fit, we look forward to meeting you and sharing more about auryx with you!