AI/ML Engineer

IC Resources; Cambridge; On-site; GBP 60,000 - 80,000; Full time

Job summary

IC Resources is looking for an On-Device ML Engineer in Cambridge to develop machine learning models for wearable devices. The role involves creating algorithms that extract reliable health signals while optimizing performance under tight constraints.

You will collaborate closely with hardware and firmware teams, tackling complex problems in health technology and having significant ownership of the algorithm development process.

This is an excellent opportunity to be part of an early-stage company with a strong growth trajectory.

Qualifications

• Strong background in signal processing and applied machine learning.
• Experience deploying ML models on embedded or edge devices.
• Proficiency in Python; C/C++ experience is a plus.
• Understanding of physiological signals and noisy, real-world sensor data.
• Ability to balance accuracy, efficiency, and robustness under hardware constraints.

Responsibilities

• Develop physiological inference algorithms for wearable health products.
• Build methods to extract reliable health metrics from real-world data.
• Advance hybrid DSP + ML approaches for continuous health sensing.

Skills

Signal processing

Applied machine learning

Python proficiency

C/C++ experience

Understanding physiological signals

Efficiency under hardware constraints

Job description

A health technology company is seeking an On-Device ML Engineer to develop machine learning models that run directly on wearable devices, extracting reliable health signals under strict real-world constraints.

This is a technically deep and highly impactful role, sitting at the intersection of signal processing, applied ML, and embedded systems. You’ll work closely with hardware and firmware teams to optimise end-to-end sensing pipelines, tackling problems that very few teams in the world are working on. You’ll have significant ownership over algorithm development from signal cleaning through to prototype integration.

In this position, you’ll develop physiological inference algorithms for wearable health products, build methods to extract reliable cardiovascular and autonomic health metrics from real-world data, and advance hybrid DSP + ML approaches for continuous health sensing — all within tight compute and power budgets.

What They’re Looking For

• Strong background in signal processing and applied machine learning
• Experience deploying ML models on embedded or edge devices
• Proficiency in Python; C/C++ experience is a plus
• Understanding of physiological signals and noisy, real-world sensor data
• Ability to balance accuracy, efficiency, and robustness under hardware constraints

Why Consider It

• Work on frontier problems in medical-grade wearable inference
• High ownership across the full algorithm pipeline, from research to integration
• Close collaboration across ML, hardware, and firmware disciplines
• Early-stage company with significant growth potential and technical influence