Labelling Project Manager
About us
Spore.Bio is a deeptech start-up born in 2023, building a new paradigm in the quality control systems in Food&Beverage, Cosmetics, and Pharmaceutics factories.
After spending a lot of time in factories environments, we saw the pain it was to make sure products were safe. Traditional quality control has heavy constraints and long waiting times. To change that, we decided to build Spore.Bio, a new generation of microbiological testing.
Our team is dedicated to bringing technology and developing a cutting-edge solution, based on advanced optical and deep-learning technologies, to detect bacterial contamination within seconds.
Spore Bio is seeking a rigorous and driven Data Labelling Lead to scale and own the annotation engine at the heart of our AI pipeline. In this role, you will be the operational and strategic backbone of how we turn raw optical imaging data into high-quality training data for our microbiological detection models. You will bridge the gap between scientific domain knowledge and ML production requirements — designing the workflows, standards, and systems that determine the quality of every model we train and the reliability of what we deliver. Join our team of R&D experts, engineers, and data scientists, and play a foundational role in building the future of industrial microbiology.
About the role
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 annotation guidelines and long-term labelling strategy are owned by our R&D team. The Labelling Project Manager's job is to carry that vision to the ground: representing it to internal and external labelling teams, ensuring it's applied consistently, and running a well-organised, well-monitored workflow day to day as the team and scope grow.
Key Responsibilities
Demand & Project Management
Intake and prioritise annotation demand from ML and R&D teams; translate into sprint-level plans
Own end-to-end annotation workflows: task scoping, assignment, QC checkpoints, and delivery
Own relationships with external annotation vendors; ensure quality and delivery stay on track
Chase down and escalate when deliverables slip; keep the process moving
Representing the Standards
Carry and represent the annotation guidelines and strategy defined by R&D to the teams doing the labelling
Flag ambiguity or edge cases back to R&D rather than resolving them unilaterally
Dashboard & Metrics
Own and maintain the annotation dashboard and KPI tracking
Escalate quality or capacity risks proactively
Team Coordination
Work closely with the QC Specialist and internal/external labelling teams
Build simple tools to streamline requests when needed (e.g. Google Forms)
About you
Master's degree in Bioinformatics, Biotechnology, Data Science, or a related field or a Bachelor's with strong, demonstrated motivation and relevant experience
3-4 years in project management, ideally with a data or technical component (prior experience specifically in data labelling is a plus, not a requirement)
Comfortable operating in a scientific or biological environment, without needing deep technical expertise
Highly organised and rigorous, the kind of person who takes notes in meetings and sends a recap without being asked
Resourceful and comfortable with everyday office and productivity tools (e.g. able to put together a simple form or tracker); no need for advanced technical skills
Strong communicator, able to bridge scientific and technical teams
Comfortable with ambiguity in an early-stage, fast-growing environment
Assertive enough to push back and hold teams accountable when deliverables slip
English and French fluent
Soft Skills & Mindset
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
Why joining us?
• Work in an innovative and rapidly growing startup.
• 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!
Recruitment process
Fit interview (~30 min): A call to get to know each other, your experience, what drives you, and what you're looking for. It's also your chance to ask anything about Spore.Bio and the role.
Technical case study (take-home+ presentation): A hands-on challenge reflecting the kind of problems you would face: annotation workflow design, demand prioritisation, quality system setup, and handling ambiguous edge cases at scale. We care about your reasoning and your instincts, not textbook answers.
On-site interview Lab visit + Founders meeting: You will meet the founders, visit the lab, and see Louis in action.
- Department
- Machine Learning Team
- Locations
- Paris
- Remote status
- Hybrid
- Employment type
- Full-time