AI/ML Engineer

AI/ML Engineer Overview

An early-stage health technology business is hiring an on-device machine learning engineer to build models that run directly on wearable products and help uncover reliable health signals in highly constrained real-world settings. The role sits at the intersection of signal processing, applied machine learning, and embedded systems, and it offers the chance to work on technically demanding problems that are uncommon across the industry.

You will be part of a team developing medical-grade wearable inference capabilities, with responsibility for improving the sensing pipeline from raw data handling through to prototype integration. The work involves close coordination with hardware and firmware specialists, and it requires careful engineering to ensure the algorithms remain accurate, efficient, and robust while operating within strict limits on power and compute.

What you will do

• Build machine learning models that can run directly on wearable devices and generate dependable health-related outputs in real-world conditions.
• Develop physiological inference methods for wearable health products, covering the full path from signal cleaning to prototype integration.
• Create techniques for deriving cardiovascular and autonomic health metrics from noisy data gathered outside controlled environments.
• Improve continuous health sensing by combining digital signal processing methods with machine learning approaches.
• Work alongside hardware and firmware teams to refine the complete sensing workflow end to end.
• Engineer solutions that fit within tight embedded-device limits for processing power, memory, and energy use.
• Take ownership of algorithm development and contribute directly to the technical direction of the product.
• Tackle difficult problems in embedded AI, signal analysis, and wearable health inference.

What they are looking for

• A solid background in signal processing together with applied machine learning.
• Experience putting machine learning models into production on embedded or edge hardware.
• Strong Python programming ability.
• Experience with C or C++ would be an advantage.
• Knowledge of physiological signals and the realities of working with noisy sensor data from the real world.
• The ability to weigh up accuracy, efficiency, and robustness when designing solutions for constrained hardware.

Why this role stands out

• You will work on frontier-level problems in medical wearable inference.
• The position offers substantial ownership across the entire algorithm pipeline, from research and development through to integration.
• You will collaborate closely with specialists across machine learning, hardware, and firmware.
• The company is early in its growth journey, which means there is strong potential for impact and technical influence.
• The package includes a salary of £80k and hybrid working.

How to apply

Interested candidates are invited to apply now. For more information, you can contact Charles Duran, the specialist handling this opportunity, by phone or email.

Job ID: 452672.

Degree Requirement: Not Specified

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