At a Glance
- Tasks: Lead the development of machine learning models to interpret brain signals and improve patient care.
- Company: Join CoMind, a pioneering tech company transforming clinical brain monitoring.
- Benefits: Enjoy equity options, unlimited holiday, mental health support, and free meals.
- Why this job: Make a real impact on healthcare by developing cutting-edge neuromonitoring technologies.
- Qualifications: Experience in machine learning, Python, and a passion for interdisciplinary collaboration.
- Other info: Work in a dynamic environment with opportunities for professional growth and learning.
The predicted salary is between 42000 - 60000 ÂŁ per year.
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.
Responsibilities- 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 (+ bank holidays) and one week of remote working per quarter.
- Free lunch twice per week via JustEat and free dinner on those days when you need to work later.
- Twice weekly deliveries of fresh fruit and a comprehensive selection of snacks and drinks.
- YuLife subscription, allowing you to convert daily steps and meditation into discounts at a range of stores.
- Access to Udemy for upskilling and professional development.
Senior Machine Learning Engineer employer: CoMind
Contact Detail:
CoMind Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to machine learning and neuromonitoring. You never know who might have a lead on your dream job or be looking for someone just like you.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving time-series data and machine learning. Share your GitHub link when you apply through our website, so potential employers can see your coding chops and problem-solving skills in action.
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python skills and understanding of signal processing concepts. Practice explaining your past projects and how they relate to the role at CoMind, as this will help you stand out during the interview process.
✨Follow Up
After your interview, don’t forget to send a thank-you email! It’s a great way to express your appreciation and reiterate your interest in the position. Plus, it keeps you fresh in their minds as they make their decision.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with time-series data and any relevant projects that showcase your skills in machine learning and signal processing.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about neuromonitoring technology. Share specific examples of how your background aligns with our mission to improve brain disorder diagnosis and treatment.
Showcase Your Technical Skills: Don’t forget to mention your fluency in Python and any industry-standard tools you’ve used. We want to see your expertise in action, so include examples of high-quality code or projects you've worked on.
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 at CoMind!
How to prepare for a job interview at CoMind
✨Know Your Stuff
Make sure you brush up on your machine learning and signal processing concepts. Be ready to discuss your experience with time-series data and how you've applied ML techniques in past projects. This role is all about interpreting complex datasets, so showing your expertise will definitely impress.
✨Showcase Collaboration Skills
Since this position involves working closely with clinicians and engineers, be prepared to share examples of how you've successfully collaborated in cross-disciplinary teams. Highlight any experiences where you translated technical requirements into actionable insights for non-technical stakeholders.
✨Demonstrate Problem-Solving Abilities
Think of specific challenges you've faced in previous roles, especially related to data analysis or algorithm development. Be ready to explain your thought process and the steps you took to overcome these challenges. This will show that you can think critically and adapt in a fast-paced environment.
✨Prepare Questions
Have a few thoughtful questions ready about the company's projects, team dynamics, or future goals. This not only shows your interest in the role but also gives you a chance to assess if the company is the right fit for you. Plus, it opens up a dialogue that can make the interview feel more like a conversation.