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

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

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About this role

Principal Machine Learning Engineer - Applied AI & LLMs (x/f/m) Paris, Paris, France What you'll do We are looking for a Principal Machine Learning Engineer to join the DS & AI organization at Doctolib. This is a transversal force multiplier role operating across all AI teams: Clinical, Productivity, Phone Assistant and ASR. Rather than working within a single feature team, you will own the cross-cutting technical challenges: defining how Doctolib's product and AI teams build agentic solutions, standardizing ML evaluation frameworks, and spreading strong engineering practices across the org. You will unblock teams, shape architecture decisions, and take on the deep technical work that requires senior ML judgment at scale, directly impacting the daily lives of 400,000 healthcare professionals and the health of 80 million patients. Building at Doctolib means delivering innovative products that measurably improve outcomes for care teams and patients alike. Technical Strategy & Architecture - Own cross-team ML architecture decisions, from model selection to production deployment patterns and strategic build vs. buy decisions - Define and drive adoption of rigorous evaluation frameworks across all AI teams, setting the standard for how Doctolib measures model and agentic performance - Establish shared production infrastructure patterns for AI: model and prompt versioning, guardrails, uncertainty quantification, cost optimization, and observability - Lead the technical design of agentic solutions and define how product teams across Doctolib build on top of AI capabilities - Elevate technical standards across the DS & AI org by influencing Staff and Senior ML Engineers through architecture reviews,

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