Senior AI/ML Engineer, On-Device LLM for Neuro Monitoring

Senior AI/ML Engineer, On-Device LLM for Neuro Monitoring

Full-Time 65250 - 79750 Β£ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Integrate on-device LLM for neuromonitoring and optimise performance in a regulated medical context.
  • Company: CoMind, a pioneer in non-invasive neuromonitoring technology.
  • Benefits: Flexible remote work, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative environment in Kings Cross with a focus on impactful projects.
  • Why this job: Make a real difference in brain disorder diagnosis and treatment with cutting-edge technology.
  • Qualifications: Experience in AI/ML engineering and a passion for healthcare innovation.

The predicted salary is between 65250 - 79750 Β£ per year.

CoMind is building non-invasive neuromonitoring technology to improve brain disorder diagnosis and treatment. As a Senior Software Engineer on the CoVision project, you will integrate an on-device LLM, ensure safety and reliability, and optimize performance for constrained hardware in a regulated medical context.

You will work from our Kings Cross offices at least 4 days a week with a flexible remote day, collaborating with hardware, product and clinical teams to deliver clinically impactful solutions.

Senior AI/ML Engineer, On-Device LLM for Neuro Monitoring employer: Jackalope Digital LLC

At Anthropic, we pride ourselves on fostering a collaborative and innovative work culture that empowers our engineers to make a real impact. Located in vibrant London or San Francisco, we offer competitive benefits, continuous learning opportunities, and a commitment to employee growth, ensuring that you can thrive both personally and professionally while working on cutting-edge connectivity infrastructure.

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Contact Details:

Jackalope Digital LLC Recruitment Team

We think you need these skills to ace Senior AI/ML Engineer, On-Device LLM for Neuro Monitoring

Machine Learning
Natural Language Processing
On-Device LLM Integration
Safety and Reliability Engineering
Performance Optimisation
Embedded Systems
Collaboration with Cross-Functional Teams