Senior Engineering Manager - Voice Teams

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

1. Recruiter Call (30 min)
2. Hiring Manager Interview - in-depth discussion on people management approach and leadership experience
3. System Design Interview (SDI) - assess architectural thinking and ability to challenge complex ML systems
4. Behavioral Interview (BHV) - assess leadership, decision-making in ambiguity, and management philosophy
5. Offer