Data Labeling Lead
Role details
Job location
Tech stack
Job description
Our core mission is to develop AI-powered detection of microbiological entities on optical data. High-quality, reproducible annotations are the foundational input to every model we train. The Data Labelling Lead will own this function end-to-end: translating scientific needs into annotation strategies, ensuring process rigor, and building a scalable, well-governed workflow as the team grows. You will lead, operate, and continuously improve the annotation engine that powers our ML models., Process & Strategy
- Define and maintain annotation guidelines and labelling schemas for optical/microbio datasets
- Own end-to-end annotation workflows: task scoping, assignment, QC checkpoints, delivery, and feedback loops
- Anticipate bottlenecks and drive continuous optimisation as the team and scope scale
Demand & Project Management
- Intake and prioritise annotation demand from ML and R&D teams; translate into sprint-level plans
- Own relationships with external annotation vendors; ensuring excellence in quality and delivery
- Track progress and report delivery status to stakeholders
Dashboard & Metrics
- Own the annotation dashboard and define KPIs; escalate quality or capacity risks proactively
Team Leadership
- Line-manage and mentor the QC Specialist and any future team member, * Participate in exciting and impactful projects.
- Evolve in a collaborative and stimulating work environment.
- Opportunities for professional development and continuous training.
What we offer
We believe that flexibility and trust are important parts of a company. Our work environment reflects this thanks to:
Flexible remote: If you live in Paris, you can work from our office or from your place with no constraints.
On top of that, we offer many perks such as:
- A budget for remote work equipment
- A Gymlib subscription for you to stay in shape wherever you are
- Premium health insurance (Alan in France)
- A Swile card for your meals, if you are based in France
- Frequent team events and in-person gatherings every quarter!
Requirements
Do you have experience in Scripting?, * MSc or Engineering degree in Biomedical Engineering, Bioinformatics, Computer Vision, Data Science, or related field
- 5 years in data annotation, ML data operations, or a closely related role
- Strong understanding of ML model requirements and how annotation quality affects model performance
- Exposure to biomedical microscopy, biophotonics, or life-science imaging strongly preferred
- Proven track record managing annotation/data pipelines at scale (10k+ samples or equivalent)
- Proficiency with Python scripting for workflow automation and data QC
- Experience translating complex scientific or technical requirements into clear annotation guidelines
- Familiarity with at least one annotation platform (CVAT, Label Studio, Labelbox, Scale AI, etc.)
- Experience designing and maintaining annotation dashboards and KPI tracking systems, * Strong project management capabilities; able to handle multiple concurrent workstreams
- Excellent communicator bridging scientific domain experts and ML engineers
- Systematic thinker with a continuous-improvement mindset
- Comfortable with ambiguity in early-stage, research-driven environments
- Proven ability to mentor and lead specialists