Cofounder CTO - Digital Health (Digital Biomarkers)

As CTO and cofounder, you will lead Neuron’s technical strategy, AI/ML development, software engineering, and platform architecture. Working closely with the CEO and scientific leadership, you will translate the company’s vision into a production-ready platform built around foundation models, multimodal intelligence, and conversational AI., * AI/ML and foundation models: Lead the development and integration of AI systems leveraging foundation models, multimodal learning, and modern machine-learning architectures.

• Conversational AI: Design and build conversational interfaces, including voice-based AI companions, enabling natural, context-aware interactions and personalized engagement.
• Multimodal intelligence: Develop systems that integrate voice, motor, physiological, behavioral, and cognitive data into meaningful representations of neurological function and longitudinal patient states.
• ML engineering and deployment: Build end-to-end pipelines for data processing, model evaluation, inference, deployment, monitoring, and continuous improvement.
• Software engineering: Own the end-to-end software architecture, backend services, APIs, mobile integrations, cloud infrastructure, and engineering practices.
• AI safety and system reliability: Establish robust boundaries between generative AI and safety-critical functions through deterministic controls, auditable workflows, and appropriate safeguards.
• Clinical intelligence infrastructure: Build the data and analytics infrastructure required to support clinical research, digital biomarker development, and pharmaceutical clinical-development workflows.
• Data integration: Develop secure, scalable pipelines integrating smartphone and wearable data, including Apple HealthKit, Android Health Connect, and selected third-party devices.
• Technical leadership: Recruit and lead the initial AI/ML and software engineering team, establish development standards, and manage external technical partners.
• Technology strategy: Define the technical roadmap, prioritize development against scientific and commercial milestones, and support technical due diligence for investors and partners.

Required

• Significant experience in AI/ML engineering, applied machine learning, or software engineering, with a track record of building and deploying production-grade systems.
• Strong software engineering fundamentals across system architecture, APIs, backend development, cloud infrastructure, testing, and deployment.
• Practical experience with foundation models, including LLM integration, model orchestration, inference, evaluation, and production deployment.
• Experience developing conversational AI applications, ideally involving voice interfaces, context management, or personalized interactions.
• Experience building end-to-end machine-learning pipelines and translating research concepts into reliable software products.
• Familiarity with multimodal data processing, representation learning, or integrating heterogeneous data sources.
• Ability to combine hands-on technical execution with architectural leadership and team development.
• A founder’s mindset, with the ability to operate in an early-stage environment, make decisions under uncertainty, and build from an initial prototype.

Strongly Preferred

• Experience with multimodal foundation models, cross-modal representation learning, or sensor-based machine learning.
• Experience with speech technology, audio processing, voice interfaces, or conversational agents.
• Familiarity with retrieval-augmented generation, fine-tuning, inference optimization, and AI observability.
• Experience designing agentic or tool-using AI systems with reliable execution boundaries and auditable controls.
• Knowledge of data privacy, information security, and regulatory considerations for AI in healthcare.
• Experience in clinical intelligence, digital health, neuroscience, clinical research, or pharmaceutical technology.
• Previous experience as a CTO, technical cofounder, or early engineering leader in a startup.
• MSc or PhD in computer science, AI, machine learning, engineering, or a related technical discipline.