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 unlimited holiday, private medical insurance, and a company equity plan.
- Why this job: Make a real difference in healthcare by improving brain disorder diagnosis and treatment.
- Qualifications: 4+ years in machine learning with strong Python skills and a passion for innovation.
- Other info: Collaborative environment with opportunities for professional growth and flexible working.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Join to apply for the Senior Machine Learning Engineer role at Comind Technologies. At CoMind, we are developing a nonâinvasive neuromonitoring technology that will result in a new era of clinical brain monitoring. In joining us, you will be helping to create cuttingâedge 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 timeâseries datasets collected by our nextâgeneration neural sensor in both clinical trial and inâhouse experimental settings. You will play a key role in interpreting physiological and optical signals to derive actionable insights that inform product development and clinical decisionâmaking. 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 realâworld use. At CoMind, all team members work at least 4 days per week from our new Kings Cross offices, plus a flexible workâfromâhome day.
Responsibilities
- Lead the development and delivery of novel signal processing and machine learning models to interpret physiological signals, e.g., timeâseries regression, classification and outliers detection.
- Lead exploratory data analysis on complex timeâseries 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 highâquality, wellâtested 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 nonâtechnical 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 timeâseries, physiological signals or continuous sensor data.
- >4 years of experience in a research or applied data science role, ideally involving crossâdisciplinary 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 industryâstandard tools for version control, data engineering, CI/CD and reproducible research workflows.
- Comfortable working in a fastâpaced, researchâdriven 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 nonâtechnical stakeholders.
Nice to Have
- Experience with signal analysis and pipeline design for time series data in the context of wearable or medical products.
- Handsâon 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.
- Salaryâsacrifice 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 in London employer: Comind Technologies
Contact Detail:
Comind Technologies Recruiting Team
StudySmarter Expert Advice đ€«
We think this is how you could land Senior Machine Learning Engineer in London
âšTip Number 1
Network like a pro! Reach out to people in the industry, especially those at CoMind. A friendly chat can sometimes lead to opportunities that arenât even advertised yet.
âšTip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your machine learning projects. This is your chance to demonstrate your expertise in time-series analysis and signal processing.
âšTip Number 3
Ace the interview by being ready to discuss real-world applications of your work. Think about how your past experiences can translate into the role at CoMind, especially in clinical settings.
âšTip Number 4
Donât forget to apply through our website! Itâs the best way to ensure your application gets seen by the right people. Plus, it shows youâre genuinely interested in joining the team.
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application đ«Ą
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 our mission at CoMind. Keep it concise but impactful!
Showcase Your Technical Skills: Donât forget to mention your proficiency in Python and any industry-standard tools youâve used. We want to see your hands-on experience, so include specific examples of projects where you've applied these skills.
Apply Through Our Website: We encourage you to apply directly through our website. Itâs the best way for us to receive your application and ensures youâre considered for the role. Plus, it shows youâre keen on joining our team!
How to prepare for a job interview at Comind Technologies
âšKnow 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. This will show that youâre not just familiar with the concepts but have practical experience applying them.
âšShow 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.
âšPrepare for Technical Questions
Expect to face some technical questions or even a coding challenge during the interview. Practice writing clean, efficient Python code and be ready to explain your thought process. Familiarise yourself with industry-standard tools and methodologies, as these might come up in conversation.
âšAsk Insightful Questions
At the end of the interview, donât forget to ask questions that show your interest in the company and the role. Inquire about their current projects, challenges they face in neuromonitoring technology, or how they envision the future of brain monitoring. This demonstrates your enthusiasm and helps you gauge if the company is the right fit for you.