Senior Software Engineer - Applied AI

Join CoMind as a Senior Software Engineer in London, focusing on AI integration for neuromonitoring technology aimed at improving clinical brain care.

• AI Integration: Integrate an on-device LLM into the CoMind One system, connecting it to live neuromonitoring signals and building the query and response layer clinicians interact with.
• Model Evaluation & Reliability: Own how we measure whether the model answers the right clinical questions correctly and consistently. Build the evaluation, prompting and guard-rail approaches that keep output safe to show at the bedside.
• Systems Performance: Optimise inference performance on constrained on-device hardware, managing latency, memory and throughput within the CoMind One system.
• Medical Device Software Development: Design and develop medical device software to IEC 62304 and ISO 14971, from real-time on-device behaviour through to the interfaces clinicians touch.
• Compliance & Cybersecurity: Ensure AI deployments meet cybersecurity requirements and regulatory standards, including FDA guidance for AI/ML-enabled devices.
• Reliability & Collaboration: Keep the deployed fleet reliable, and work directly with hardware, product and clinical teams to diagnose and resolve issues quickly.
• AI is fundamental to our culture — it's not just a tool, but a core part of how we work, collaborate, and innovate. We expect all team members to embrace AI in their daily work and continuously find new ways to use it effectively.

• 7+ years of hands-on software engineering.
• Comfortable working in C++, with Python alongside it.
• Practical experience using LLMs as an applied tool: prompting, guardrails, RAG, evaluation, and reasoning about model behaviour.
• You've built, or extended a model and integrated it meaningfully into a real product, close to the surface users actually touch.
• Experience integrating third-party libraries or complex components into a larger system, ideally performance-sensitive or resource-constrained.
• Comfortable reasoning about performance: latency, memory and throughput on constrained hardware.
• Strong with Git and CI/CD.
• Edge / on-device AI: running models on constrained hardware such as Jetson, Android, iPad, Raspberry Pi or microcontrollers.
• Hands-on with llama.cpp or similar, and evaluating small on-device models (e.g. Qwen, Gemma, MedGemma, custom).
• Some hardware exposure: anyone doing genuine edge AI tends to have this.
• Cloud experience (AWS), particularly running LLMs in a cloud environment.
• A background in a regulated or safety-critical industry

• 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
• Lunch voucher (£10) every day for JustEat and free dinner on those days where you need to work later
• Twice weekly deliveries of fresh fruit and an extensive selection of snacks and drinks
• YuLife subscription, allowing you to turn your daily steps and meditation into discounts at a range of stores
• • Salary £94K – £120K • Offers Equity