At a Glance
- Tasks: Lead the development of innovative machine learning models for brain monitoring technology.
- Company: Join CoMind, a pioneering tech company transforming clinical brain monitoring.
- Benefits: Enjoy equity options, unlimited holiday, and comprehensive health support.
- Why this job: Make a real difference in patients' lives with cutting-edge neuromonitoring technology.
- Qualifications: 4+ years in data science, strong Python skills, and experience with time-series data.
- Other info: Collaborative environment with opportunities for professional growth and learning.
The predicted salary is between 43200 - 72000 ÂŁ per year.
At CoMind, we are developing a non‑invasive neuromonitoring technology that will result in a new era of clinical brain monitoring. In joining us, you will be helping to create cutting‑edge technologies that will improve how we diagnose and treat brain disorders, ultimately improving and saving the lives of patients across the world.
The Role
As a Senior ML Engineer / Senior Data Scientist at CoMind, you will join a multidisciplinary team working 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.
At CoMind, all team members work at least 4 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 outliers 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.
Skills & Experience
- Proven track record in applying machine learning / deep learning techniques for time‑series, physiological signals or continuous sensor data.
- >4 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 and quantisation, spectral analysis, etc.
- Fluent in Python and expert in industry‑standard tools for version control, data engineering, CI/CD and reproducible research workflows.
- Comfortable working 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.
Nice to Have
- 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.
Benefits
- 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 4x 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 where you need to work later.
- Twice weekly deliveries of fresh fruit and a comprehensive selection of snacks and drinks.
- YuLife subscription, allowing you to turn your daily steps and meditation into discounts at a range of stores.
- Access to Udemy for upskilling and professional development.
London, England, United Kingdom
Senior Machine Learning Engineer employer: Comind Technologies
Contact Detail:
Comind Technologies 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 neurophysiology. You never know who might have a lead on your dream job at CoMind!
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving time-series data and machine learning. Share it on platforms like GitHub or your personal website. This is your chance to shine and demonstrate your expertise to potential employers!
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python skills and understanding of signal processing concepts. Practice explaining complex ideas clearly, as you'll need to communicate effectively with both technical and non-technical team members at CoMind.
✨Apply Through Our Website
Don't forget to apply directly through our website! It shows you're genuinely interested in joining CoMind and helps us keep track of your application. Plus, you might just get noticed faster!
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 is your chance to shine! Use it to explain why you're passionate about neuromonitoring technology and how your background aligns with CoMind's mission. Keep it concise but impactful!
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Python and any industry-standard tools you’ve used. We want to see your hands-on experience with machine learning techniques and digital signal processing concepts.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and get you on board with our exciting projects at CoMind!
How to prepare for a job interview at Comind Technologies
✨Know Your Stuff
Make sure you brush up on your machine learning and signal processing knowledge. Be ready to discuss specific techniques you've used in the past, especially those related to time-series data and physiological signals. This will show that you’re not just familiar with the concepts but have practical experience applying them.
✨Show Your Collaborative Spirit
Since this role involves working closely with clinicians and engineers, be prepared to share examples of how you've successfully collaborated in cross-disciplinary teams. Highlight any projects where you translated complex technical requirements into actionable insights for non-technical stakeholders.
✨Prepare for Technical Questions
Expect some deep dives into your coding skills, particularly in Python. Brush up on writing clean, efficient code and be ready to discuss your experience with version control and CI/CD processes. You might even be asked to solve a problem on the spot, so practice coding challenges beforehand!
✨Communicate Clearly
Your ability to convey complex ideas simply is crucial. Prepare to explain your past projects and findings in a way that’s understandable to both technical and non-technical audiences. Practising this will help you stand out as someone who can bridge the gap between data science and clinical application.