Senior Machine Learning Engineer in London

At CoMind, we are developing a non‑invasive neuromonitoring technology that will usher in a new era of clinical brain monitoring. By joining us, you will help create cutting‑edge technologies that improve how we diagnose and treat brain disorders, ultimately improving and saving the lives of patients worldwide.

The role is a Senior Machine Learning Engineer / Senior Data Scientist position on a multidisciplinary team at the intersection of neurophysiology, optics, machine learning, and signal processing. Your focus will be on analysing multidimensional time‑series datasets collected by our next‑generation neural sensor in both clinical trial and in‑house experimental settings.

You will play a key role in interpreting physiological and optical signals to derive actionable insights that inform product development and clinical decision‑making. Working closely with clinicians, neurophysiologists, physicists, and engineers, you will help lead algorithm and ML model development to extract meaningful metrics of brain function, improve signal quality through advanced denoising and demixing techniques, and validate signal fidelity in real‑world use.

All team members work at least four days per week from our new Kings Cross offices, plus a flexible work‑from‑home day.

• Lead the development and delivery of novel signal processing and machine learning models to interpret physiological signals, e.g., time‑series regression, classification, and outlier detection.
• Lead exploratory data analysis on complex time‑series datasets generated from clinical trials, internal studies, and external research databases.
• Design and validate algorithms for denoising, signal demixing, and interpretation of neuromonitoring data.
• Write high‑quality, well‑tested Python code that meets industry standards.
• Collaborate with domain experts to translate clinical and physiological requirements into robust data analysis workflows.
• Deliver signal processing methodologies ready for translation into medical device products.
• Produce clear and insightful white papers, documentation, and visualisations for both technical and non‑technical stakeholders.
• Participate in research planning by gathering requirements, scoping work items, and contributing to roadmap discussions.

• Proven track record in applying machine learning / deep learning techniques for time‑series, physiological signals, or continuous sensor data.
• More than four years of experience in a research or applied data science role, ideally involving cross‑disciplinary collaboration with clinical or experimental teams.
• A deep understanding of digital signal processing concepts such as sampling, quantisation, spectral analysis, etc.
• Fluency in Python and expertise in industry‑standard tools for version control, data engineering, CI/CD, and reproducible research workflows.
• Comfort in a fast‑paced, research‑driven environment with a strong sense of ownership and a willingness to learn and experiment.
• Excellent written and verbal communication skills for conveying complex results clearly to technical and non‑technical stakeholders.

• Experience with signal analysis and pipeline design for time‑series data in the context of wearable or medical products.
• Hands‑on experience in software engineering.
• Familiarity with regulated development processes (e.g., SaMD).
• Strong understanding of neurological and cardiovascular signals.
• Strong background in biostatistics.
• Strong understanding of the physical principles associated with optical spectroscopy, interferometry, and related techniques.

• Company equity plan so all employees share in the success of the company.
• Salary‑sacrifice pension scheme.
• Private medical, dental and vision insurance (medical history disregarded).
• Group life assurance at four‑times annual income.
• Comprehensive mental health support, including unlimited access to 1:1 sessions with trained professionals.
• Unlimited holiday allowance.