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- Tasks: Develop cutting-edge ML models for wearable health devices and optimise sensing pipelines.
- Company: Innovative health tech company focused on impactful wearable technology.
- Benefits: Competitive salary, growth opportunities, and a chance to work on frontier medical problems.
- Other info: Join a dynamic team with significant ownership over algorithm development and integration.
- Why this job: Make a real difference in health tech while working with advanced ML and signal processing.
- Qualifications: Strong background in signal processing, applied ML, and experience with embedded systems.
The predicted salary is between 50000 - 70000 £ per year.
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
AI/ML Engineer employer: IC Resources
Contact Detail:
IC Resources Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Engineer
✨Tip Number 1
Network like a pro! Reach out to professionals in the health tech and AI/ML space on LinkedIn. Join relevant groups and participate in discussions to get your name out there and show off your passion for wearable technology.
✨Tip Number 2
Showcase your skills! Create a portfolio of projects that highlight your experience with signal processing and machine learning. If you’ve worked on any embedded systems, make sure to include those too. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and C/C++ skills. Practice coding challenges that focus on algorithm development and optimisation, especially under constraints similar to those in wearable devices. We want you to feel confident when it’s time to shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace AI/ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in signal processing and applied ML. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about wearable health technology and how your background makes you a perfect fit for our team. Let us know what excites you about the role!
Showcase Your Technical Skills: Since we’re looking for someone with a strong background in Python and possibly C/C++, make sure to mention any relevant projects or experiences. If you've deployed ML models on embedded devices, we want to hear about it!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Don’t miss out!
How to prepare for a job interview at IC Resources
✨Know Your Signals
Make sure you brush up on your understanding of physiological signals and how they can be affected by real-world conditions. Be ready to discuss specific examples of how you've dealt with noisy data in the past, as this will show your practical experience in signal processing.
✨Showcase Your ML Skills
Prepare to talk about your experience deploying machine learning models on embedded or edge devices. Have a couple of projects in mind where you successfully optimised algorithms for performance and efficiency, and be ready to explain your thought process during those projects.
✨Collaboration is Key
Since this role involves working closely with hardware and firmware teams, think of examples where you've collaborated across disciplines. Highlight your communication skills and how you’ve navigated technical discussions to achieve common goals.
✨Be Ready for Technical Questions
Expect some deep technical questions related to both signal processing and applied ML. Brush up on your Python and C/C++ skills, and be prepared to solve problems on the spot. Practising coding challenges related to algorithm optimisation could give you an edge.