Lead and coach two teams of ML engineers and data scientists focusing on voice and language technologies. Own the technical direction, architecture, and strategic roadmap for ASR products to reduce administrative burdens in healthcare.
What we do
At Doctolib, we are building AI-powered healthcare solutions that make a real difference in the lives of millions of patients and healthcare professionals every day. Our AI organization is at the heart of this mission, developing cutting-edge voice and language technologies that reduce administrative burden for doctors and improve patient care.
The Voice team sits within the Applied AI organization and powers three flagship AI products:
- Consultation Assistant - automatically transcribes and structures doctor-patient conversations to feed downstream NLP components (medical facts extraction, summarization)
- Clinical Dictation - real-time streaming dictation with medical vocabulary boosting and LLM-based post-processing
- Phone Assistant - AI-powered telephone assistance for medical practices, combining near-real-time ASR with conversational AI
Our stack includes state-of-the-art models (FastConformerCTC, Whisper, NeMo), modern inference infrastructure (Triton, Ray Serve, MLFlow), and spans multiple languages (French, German, and beyond).
Your role
We are looking for a Senior Engineering Manager to lead our Voice teams. This is a high-impact leadership role that sits at the intersection of applied ML research, engineering delivery, and people management.
You will directly manage 2 teams (8 engineers) working across multiple ASR product perimeters. You will be the promoter of technical decisions for your scope and a key advocate for your teams across the organization.
What you will do
People Management
- Lead, coach, and develop a team of 8 ML engineers and data scientists across 2 teams
- Own performance management, career development, and talent retention for all direct reports
- Drive a culture of high standards and fast execution
- Act as Hiring Manager: partner with Talent & People to attract and recruit top talent
Technical Ownership
- Own the technical direction of your perimeter, including architecture choices and trade-offs
- Maintain full visibility across all technical domains covered by your teams, with no blind spots
- Deeply understand system design and architectural constraints to challenge and guide your teams effectively
- Ability to deeply understand architectures, challenge technical decisions, assess trade-offs, and ensure your teams are building the right things the right way
Strategy & Delivery
- Define and drive the roadmap for your teams in alignment with organizational OKRs
- Navigate ambiguity and make fast, informed decisions in a constantly evolving scope
- Identify synergies across teams and ensure technical coherence across the ASR perimeter
- Contribute to broader Applied AI initiatives as a senior engineering leader
What we are looking for
Must have
- 3+ years of people management experience leading ML or Data Science engineering teams
- Strong technical background in Machine Learning (classical ML is a must)
- Ability to understand, challenge, and make architectural decisions on complex ML systems (at a level benchmarked against leading industry standards)
- Deep understanding of system design, trade-offs, and technical risk management
- Experience thriving in a startup-like environment: fast decisions, ambiguity, frequent scope changes
- Versatile profile, comfortable operating across multiple technical domains simultaneously
- Fluent in English; French is a plus
Nice to have
- Hands-on experience with ASR, speech processing, or audio ML
- Familiarity with LLMs and their integration into production ML systems
- Experience managing multi-team organizations or acting as a manager of managers
What we offer
- Join our mission to improve access to healthcare across the world and have a meaningful impact on millions of people every day
- A decisive leadership role with real ownership from day one
- The opportunity to work on cutting-edge AI at the intersection of voice, LLM, and medical technology
- A strong engineering culture with high standards and a bias for impact
- Continuous development opportunities: learning programs, knowledge sharing, internal mobility
- Full remote flexibility
- Competitive compensation and benefits package
The interview process
- Recruiter Call (30 min)
- Hiring Manager Interview - in-depth discussion on people management approach and leadership experience
- System Design Interview (SDI) - assess architectural thinking and ability to challenge complex ML systems
- Behavioral Interview (BHV) - assess leadership, decision-making in ambiguity, and management philosophy
- Offer