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Doctolib

Senior Machine Learning Engineer - Orchestration - Applied AI & LLMs (x/f/m)

Hybrid

Part remote, part office, you need to live within commuting distance of a named location.

Hybrid · Paris

Employer listed it 3 months ago · Added 4 days ago

Been open since 3 months ago. Long-running listings are sometimes left up after the role is filled.

Salary

Not stated

Location

Hybrid · Paris

Timezone

Not stated

Contract

Contract

Experience

Senior

Category

Data

This employer didn't state pay. Jobs like this usually pay around $145k–$210k a year, a typical range taken from 255 senior-level data roles on Nomaders that do state pay. It's a guide, not an offer.

Remote flexibility

Hybrid

This role is only partly remote, the employer expects time in the office around Paris, Hybrid, so you need to live within commuting distance.

What the employer says

  • Source listing states candidate location: "Paris, Hybrid"
  • Listing mentions "Hybrid"

What Nomaders makes of it

  • Not suitable if you plan to move between countries

The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.

About the role

Set a new pulse for healthcare!

We are looking for a Senior Machine Learning Engineer to join the Orchestration team in AI Health Assistant .

Your mission will be to ensure our AI Health Companion behaves safely, reliably, and helpfully — for millions of patients and practitioners. You will work in a cross-functional team building robust evaluation pipelines for agentic AI systems, contributing directly to improving the quality and safety of AI-powered healthcare.

Working in the tech team at Doctolib means building innovative products and features to improve the daily lives of care teams and patients.

What you'll do

Your responsibilities include but are not limited to:

Define and own the evaluation strategy for our AI agentic system — metrics, protocols, datasets, and tooling

Implement and maintain automated evaluation pipelines to monitor model quality, safety, and alignment across iterations

Run systematic experiments to assess reasoning, factuality, robustness, and user experience

Collaborate closely with model developers and research scientists to provide insights and drive iterative improvement

Contribute to research and internal knowledge sharing on LLM evaluation methodologies and best practices

Life at Doctolib Tech

Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to country and healthcare specialty requirements.

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 .

Want to learn more about our tech culture and environment? Visit the Doctolib Tech site .

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'll be a great fit if you:

Hold an MSc or PhD in Computer Science, Machine Learning, Data Science, or a related field

Have 7+ years of hands-on experience working with large language models (e.g., GPT, Claude, Llama, or BERT-like architectures)

Have proven experience evaluating agentic or reasoning systems (e.g., autonomous agents, tool-using LLMs, dialogue systems, or task-oriented assistants)

Have a strong track record in experiment design, metric definition, and evaluation automation

Are able to bridge research and production, influencing both modeling and product decisions

Requirements

The employer hasn't listed requirements separately, they're described in the role summary above and on the original listing.

Benefits

  • ·Free comprehensive health insurance (basic package) 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

How to apply

  1. 1Check the flexibility label above, hybrid, matches where you plan to live and work.
  2. 2Tailor your CV to the role at Doctolib, mentioning your remote working experience.
  3. 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.

Found 5d ago. Last checked 23 Sept. Always confirm the details on the original posting, salary and location can change after publication.

Listing sourced from Company boards.

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