Deep Learning Engineer, Implicity

• As we are searching for a Junior / Confirmed Deep Learning Engineer:
• Must have:
• At least one experience ui Data Science or Deep Learning
• Education: A Master's degree, Engineering degree, or PhD in a relevant field such as Data Science, AI, Applied Mathematics, or a related discipline
• Hands-on experience with Python and Deep Learning frameworks
• Excellent theoretical knowledge of Deep Learning foundations (gradient flow, back-propagation, and network architecture logic), and associated mathematical base
• Good understanding of self-supervised learning or generative modelling
• Professional proficiency in French and English

Desirable

• We are hiring a Deep Learning Engineer (Junior/Confirmed level) to join the Software as Medical Device (SaMD) squad
• At Implicity, we're transforming the management of cardiac conditions providing innovative AI-powered medical devices. Our squad is building, deploying and maintaining advanced solutions that empower healthcare professionals, optimise their workflows, and ultimately improve patient lives
• As part of our skilled and collaborative team, you’ll have the opportunity to translate varied and complex data into clinically impactful projects in an environment where we promote continuous learning, innovation and knowledge sharing, providing dedicated time for experimentation and professional development
• 🤝 Reporting structure:
• Direct report: Marika (Data Scientist Manager)
• Collaboration: You will work closely with the SaMD squad (Data Scientists and ML Engineers), the Clinical team for medical relevance, and the Product Manager for roadmap alignment. Cross-functional collaboration is at the heart of how we operate
• 🧠 Your missions:
• Contribute to the research, development and validation of:
• State-of-the-art Deep Learning architectures (Transformers, Temporal CNNs) for various time-series data from Cardiac Implantable Electronic Device (CIED) signals
• Self-Supervised Learning pipelines to leverage our database of over 100,000 patients
• Exploring the SNDS data via the Health Data Hub
• Ensure the reproducibility, scientific correctness and transparency of each experiment, and medical relevance of our AI projects for both patients and caregivers
• Collaborate with our Clinical team on scientific publications

• 1st HR Contact with Astrid (Talent Acquisition Manager) – 45 min - G-meet
• Job / Manager Interview with Marika (Data Scientist Manager) – 45 min - G-meet
• Technical Interview with two members of the SaMD squad – 90 min - On-site
• Vision Alignment with Alex (SaMD Product Manager) and Arnaud (CEO) – 1h - On-site
• Reference Check & Offer (usually follows within 72 hours 🤞)
• Depending on your availability, the recruitment process should last less than 3-4 weeks