💙 Implicity is a digital MedTech company that brings outstanding innovations to cardiologists, powered by Big Data and Artificial Intelligence.

Thanks to our leading cardiac remote monitoring platform, it’s easier to manage data and predict patient issues, enabling cardiologists to provide the best care at the right time.

To put it simply, when you join Implicity, you’ll contribute to saving lives with us. 💓🩺

Dr Arnaud Rosier (cardiologist and AI researcher) and David Perlmutter (engineer and entrepreneur) co-founded Implicity in 2016.

• Ten years on, a French start-up/scale-up is a real game changer in the healthcare market, shaping the future of cardiology.
• 250+ hospitals / medical centers are already using our solutions, covering 100,000+ patients.

At Implicity, you will find the greatest experts in data science, engineering, clinical, regulatory, IT, sales, customer success, and more, working together. This amazing team has established Implicity as a clear European leader, and we will soon achieve the same in the US market.

Thanks to Implicity:

• Patients receive far better care
• Doctors’ lives are easier; they can focus more on prevention and treatment, rather than administration/data burden
• Healthcare payers (Social Security in France) pay a lower price by preventing/monitoring instead of treating/hospitalizing

It can start as soon as you can!

We are hiring a Deep Learning Engineer Intern to join the Software as Medical Device (SaMD) squad for a 6-month end-of-study internship. At Implicity, we’re transforming the management of cardiac conditions through innovative AI-powered medical devices.

Your mission: You will join a high-impact research project focused on Deep Learning on large datasets of Cardiac Implantable Electronic Device (CIED) signals. This internship aims to develop large cardiac data models and assess their ability to generalise across multiple clinical tasks. It includes:

• Research and implement state-of-the-art Deep Learning architectures (Transformers, Temporal CNNs) for long time-series data.
• Contribute to developing self-supervised learning pipelines to leverage our database of over 100,000 patients.
• Fine-tune and evaluate these learned representations on specific clinical diagnostic tasks (arrhythmia detection, patient risk stratification).

Must have:

• Education: final year of a Master’s degree or Engineering degree 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 the associated mathematical base
• Professional proficiency in French and English

Bonus points:

• Good understanding of self-supervised learning or generative modelling
• Experience with time-series analysis or bio-signal processing (ECG, EGM, EEG)
• Familiarity with distributed training or handling large datasets in cloud environments
• Prior experience in the healthcare industry

Your growth is our priority: We strongly encourage you to apply even if your experience doesn’t perfectly align with every point listed. We value diverse backgrounds, a growth mindset, and a passion for learning and contributing to our mission.

This isn’t a shadowing internship. You will be a full member of the SaMD squad, working on real-world medical data with a high degree of autonomy and expert mentorship.

Recruitment process

1. HR discovery call (G-meet): 20-30 min with our Talent Acquisition team
2. Technical interview (on site): 90 min with two members of the SaMD squad including your future mentor
3. Offer and alignment on start dates and expectations

We move fast when we find the right fit 🚀

Ready to make a meaningful impact? Apply now!

General information

Salary

• For this internship, you have a fixed monthly stipend of 1,200€

Benefits

• Lunch voucher: 9€ (50% employer contribution)
• Transport: 50% of your pass or a sustainable mobility pass
• 1 day off per month, cumulative over the 6 months of the internship

Remote work & Location

• Up to 3 days per week (progressively)
• Location: 29 rue du Louvre, 75002, Paris