Chief Technology Officer

Metric Bio is partnered with an emerging start-up in Oxford, UK, to hire their first ever CTO.

You'll be joining a business that are creating telepathic and empathic AI - via wearables that translate brainwaves into text in real-time - to enable healthcare as personal as our thoughts and feelings.

Nearly 1.5 billion people face health conditions and impairments rooted in thoughts and emotions, including speech impairments, chronic pain, addiction, overeating, anxiety, depression and insomnia. Given the staggering advancements in what LLMs can do with words, imagine if they could access the words in our heads—without surgery, speaking, typing or tapping.

This breakthrough could harness the incredible power of these models to alleviate suffering at Internet speed and scale.

About the role

The CTO will help build and lead an engineering team on our science foundations and insights to demonstrate a series of breakthrough capabilities on a range of wearables. Initially we will be in an R&D phase - to test and define the limits of what is possible - and then move into production. Our CTO will be instrumental in both the technology strategy and execution and will help shape the company’s path.

Key responsibilities

Collaborate: Partner with the Chief Science Officer to translate cutting-edge neuroscience into real-world applications.
Lead: Help build and inspire a lean team of neural data researchers, machine learning modelers and software engineers to move fast while staying aligned and motivated.
Architect: Design a scalable platform to go from experiments to demos to products.
Develop: Roll up your sleeves and write code, set up infrastructure, and tackle technical challenges.
Execute: Oversee the collection and processing of neural data from wearables, designing and deploying AI pipelines and ensuring data security and compliance.

Some of the key criteria we'll be looking for in our CTO:

Proven experience designing and overseeing neurotechnology data acquisition systems, including EEG and fNIRS.
Familiarity with hardware selection, electrode/sensor configurations, signal integrity monitoring, and integration with experimental control systems.
Understanding of the challenges and trade-offs in mobile, wearable, or lab-based neurodata collection.
AI/ML: Hands-on experience deploying AI-driven solutions in real-world scenarios— ideally across multiple ventures in health or neurotech—with proficiency in deep learning frameworks (TensorFlow, PyTorch) and expertise in biomedical signal processing and relevant libraries.
Data Engineering: Strong skills in building and managing robust data pipelines for biomedical signals, preprocessing noisy, high-dimensional neurodata, and handling large-scale datasets using tools like Pandas, NumPy, SciPy, MNE, and TensorFlow/Keras or PyTorch.
Wearables: Understanding of how AI models interact with wearable biosensors, embedded systems, and real-time decoding architectures. Familiarity with challenges in acquiring high-quality neurodata from non-invasive consumer-grade sensors.

To learn more, drop me an email or 'apply' today!

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