Machine Learning Ops Intern
il y a 2 semaines
We are looking for a Machine Learning Operation Intern to join the Machine Learning Platform team of Doctolib. Doctolib operates state-of-the-art medical speech recognition models that power products such as our Consultation Assistant, Medical Dictation, and Telephone Assistant. These models run in both batch and real-time streaming modes. While the batch infrastructure is already robust and widely deployed, the streaming stack is less mature and needs to evolve into a scalable, production-grade system. As a Machine Learning Operation Intern, your mission will be to design and implement the next generation of our real-time speech infrastructure. Your responsibilities include but are not limited to: Conduct standardization initiatives across several projects leveraging speech technologies Lead MLOps initiatives for real‑time speech AI Design and implement distributed, fault‑tolerant streaming inference components Set up model serving, autoscaling and rollout strategies Build a secure, high-performance system that can support large-scale usage Benchmark throughput, reliability and fault tolerance We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here and learn about our first AI hackathon here You can also discover the topic you might work on during your internship here (topic 12). Who you are Before you read on, if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply. You are a Master's student with practical experience working on ML problems You are very proficient in Python You are enthusiastic about collaborative work You are eager to ask questions, admit mistakes, and learn new things You are interested in improving healthcare through technology You are fluent in English and French What we offer A flexible workplace policy offering both hybrid and office-based mode Lunch voucher with Swile card Work Council subsidy to refund part of sport club membership or creative class Reimbursement of public transportation The interview process An interview with our Talent Partner (30 minutes) A coding interview with the Hiring Manager (1 hour 30) Job details Internship Duration: 6 months Working mode: Hybrid - 3 days a week at the office If you would like to find out more about tech life at Doctolib, feel free to read our latest Medium blog articles At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination. The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, disability. To ensure equal opportunities, we invite you to exclude personal information (e.g. pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process. Join us in building the healthcare we all dream of All information provided is processed by Doctolib for application management. For data processing details, click here. Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights. #J-18808-Ljbffr
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Machine Learning Ops Intern
il y a 2 semaines
Paris, Île-de-France Doctolib Temps pleinWe are looking for a Machine Learning Operation Intern to join the Machine Learning Platform team of Doctolib. Doctolib operates state-of-the-art medical speech recognition models that power products such as our Consultation Assistant, Medical Dictation, and Telephone Assistant. These models run in both batch and real-time streaming modes. While the batch...
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Machine Learning Ops Intern
il y a 2 semaines
Paris, France Doctolib Temps pleinWe are looking for a Machine Learning Operation Intern to join the Machine Learning Platform team of Doctolib. Doctolib operates state‑of‑the‑art medical speech recognition models that power products such as our Consultation Assistant, Medical Dictation, and Telephone Assistant. These models run in both batch and real‑time streaming modes. While the...
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il y a 1 semaine
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