Remote Data Labelling & Workflow Lead

Spore; Paris; Hybride; EUR 65 000 - 90 000; Plein temps

Avantages offerts par ce poste

Remote work equipment budget

Gymlib subscription

Premium health insurance (Alan in FR)

Swile meal card (France)

Frequent team events

Résumé du poste

Spore.Bio in Paris is seeking a Data Labelling Lead to scale our annotation engine at the heart of our AI pipeline. You will bridge scientific domain knowledge with ML production requirements, designing workflows and standards that ensure high-quality training data for our microbiological detection models.

You will own end-to-end annotation processes, coordinate with ML, R&D, and external vendors, and build simple tools to streamline requests while maintaining KPI dashboards.

Qualifications

• Master's degree or Bachelor's with motivation and relevant experience.
• 3–4 years in project management, ideally with a data or technical component.
• Experience in data labelling is a plus, not required.
• Comfortable in scientific/biological environments.
• Excellent organizational skills and precise note-taking.
• Strong communication to bridge scientific and ML teams.
• Fluent in English and French.

Responsabilités

• Manage intake and prioritisation of annotation demand from ML and R&D teams.
• Own end-to-end annotation workflows including scoping, assignment, QC, and delivery.
• Manage relationships with external vendors and ensure quality and delivery.
• Escalate delays and keep the process moving.
• Represent annotation guidelines and strategy to labelling teams.
• Maintain the annotation dashboard and KPI tracking.
• Coordinate with QC Specialist and labelling teams; build simple tools when needed.

Connaissances

Project management

Communication

Organizational skills

English & French

Formation

Master's degree in Bioinformatics/ Biotechnology/ Data Science or related field

Bachelor's degree with motivation and experience

Outils

Google Forms

Description du poste

Spore.Bio in Paris is seeking a Data Labelling Lead to scale our annotation engine at the heart of our AI pipeline. You will bridge scientific domain knowledge with ML production requirements, designing workflows and standards that ensure high-quality training data for our microbiological detection models.

You will own end-to-end annotation processes, coordinate with ML, R&D, and external vendors, and build simple tools to streamline requests while maintaining KPI dashboards.