Senior Machine Learning Engineer - Voice Model(ASR/STT) - AI Teams (x/f/m)

Doctolib
Paris, Paris, FrancePosted 30 March 2026

Job Description

What You will Do We are looking for a Senior Machine Learning Engineer to join the Voice Model (ASR/STT) engineering team in AI Clinical Products . As a Senior Machine Learning Engineer, your mission will be to deliver the ASR backbone that powers our AI products, helping health professionals save time on documentation and focus more on patient care. You will be working in a feature team developing the speech recognition technology for Doctolib's AI-powered solutions including Consultation Assistant and Phone Assistant. Working in the tech team at Doctolib involves building innovative products and features to improve the daily lives of care teams and patients. We work in feature teams in an agile environment, while collaborating with product, design, and business teams. Your responsibilities include but are not limited to: Deliver the ASR roadmap end-to-end: model design, training, evaluation, and product integration for medical-grade speech recognition Partner with MLOps to ensure training and inference pipelines are scalable, cost-efficient, and reliable in production Collaborate with product, design, and clinical teams to translate user needs into measurable technical objectives Drive continuous improvements to WER, medical term error rate, latency, diarization, domain adaptation, and multilingual performance About our tech environment Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to the country and healthcare specialty requirements. To address these challenges, we are modularizing our platform run in a distributed architecture through reusable components. Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native. 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! 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 have a Master's or Ph.D. degree in Computer Science, Data Science, or a related field You have at least 5 years of experience in ML with deep expertise in ASR/Speech-to-Text (end-to-end or hybrid), including streaming STT and real-time constraints You have hands-on experience with modern speech stacks: CTC/Transducer/Attention, Conformer/Whisper-style models, tokenizer/LM integration, diarization, and voice activity detection You have strong PyTorch skills and production ML experience: model serving, monitoring, A/B testing, rollback, and incident response in partnership with MLOps You are fluent in English Now it would be fantastic if you have: Experience with multilingual ASR, on-device or low-latency inference, telephony audio, or medical domain adaptation A passion for pushing the boundaries of speech recognition and AI in healthcare What we offer Free comprehensive health insurance for you and your children 25 days of paid vacation per year, plus up to 14 days of RTT Free mental health and coaching services through our partner Moka.care Work from abroad for up to 10 days per year thanks to our flexibility days policy Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib A subsidy from the work council to refund part of the membership to a sport club or a creative class 50% reimbursement of your public transport subscription Parent Care Program: receive one additional month of leave on top of the legal parental leave For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support Relocation support in case of international mobility Access to the best AI tools for coding, development and dedicated training The interview process HR Screen Technical Deep Dive System Desig ... (truncated, view full listing at source)
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