Senior Computer Vision Data Scientist

About us
Spore.
Bio is a deeptech startup building a new generation of microbiological quality control for the Pharmaceutical, Food & Beverage, and Cosmetics industries. Traditional microbiology methods require long incubation times before manufacturers can make critical decisions about product safety and quality. At Spore.
Bio, we are developing a radically faster approach combining microbiology, advanced optical technologies, and machine learning to detect and characterize microbial contamination. We are looking for a Senior Computer Vision Data Scientist to join our Machine Learning team and lead the deployment and adaptation of our computer vision models to real-world operational constraints. You will work at the intersection of machine learning, microbiology, hardware, and product development, helping turn our models into robust solutions used in industrial environments.

About the role
As a Senior Computer Vision Data Scientist, you will own the path of our computer vision models from data acquisition to production.
• End-to-End Data Understanding: Build a thorough understanding of the data generation pipeline, from sample preparation to downstream processing.
• Model Deployment: Deploy and adapt our computer vision models to meet field constraints and production requirements.
• Data Acquisition Strategy: Plan data acquisition hand in hand with microbiologists, taking field constraints into account, and define the data needed to improve model training and generalization.
• Model Development & Evaluation: Train, validate, and benchmark machine learning models, and perform detailed error analysis to guide improvements.
• Workflow Optimization: Identify bottlenecks and propose improvements to data workflows to accelerate model development.
• Cross-Functional Collaboration: Work closely with R&D engineers, product managers, and customers in a multidisciplinary environment.
• Technical Leadership: Mentor and guide junior team members, fostering technical growth and best practices. About you We are looking for someone with strong computer vision expertise and a track record of taking models to production.
• Academic Background: Master's degree or PhD in Data Science, Computer Science, Engineering, or a related field.
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Experience:
4+ years of professional experience in Computer Vision and/or Deep Learning, with a proven track record of deploying models to production.
• Deep Learning Frameworks: Proficiency with PyTorch or similar deep learning frameworks.
• Vision Architectures: Solid understanding of modern neural network architectures for vision tasks, such as Vision Transformers, segmentation networks, or CycleGANs.
• Production Mindset: Experience deploying ML models in production environments and handling operational constraints.
• Data & Backend Tools: Familiarity with data processing and backend tools such as pandas or FastAPI. Exposure to cloud environments (AWS, GCP, or Azure) is a plus.
• Code Quality: Strong coding fundamentals and clean code practices.
• Mentorship: Demonstrated ability to mentor and guide junior data scientists.
• Cross-Functional Mindset: Comfortable contributing in multidisciplinary environments, including client-facing and cross-functional discussions.
• Autonomy & Ownership: Proactive and execution-oriented, you take ownership and make things happen. You do not need to have worked on exactly the same technology as us. We care about scientific depth, intellectual curiosity, ownership, and your ability to solve difficult problems. Why join us?
• Work on a technology that could fundamentally change how microbiological quality control is performed.
• Solve challenging problems at the intersection of computer vision, microbiology, photonics, and industrial applications.
• Take ownership of models with a direct path from the laboratory to real customer environments.
• Join a multidisciplinary team of microbiologists, engineers, data scientists, and product experts.
• Grow through professional development and continuous learning opportunities.

What we offer
We believe flexibility and trust are important parts of our working environment.
• Flexible working arrangements and access to our Paris office and laboratories.
• Budget for remote work equipment.
• Gymlib subscription.
• Premium health insurance (Alan in France).
• Swile meal card for employees based in France.
• Frequent team events and company gatherings. Recruitment process
• 30-minute call with the Hiring Manager.
• Technical case study followed by a 45-minute debrief with members of the team.
• 1-hour Founders interview.
• Reference calls. You may also be invited to meet additional team members and visit our laboratories. This role is particularly suited to someone who wants to stay hands-on with computer vision while taking ownership of how models perform in the real world. You will have the opportunity to shape how our machine learning capabilities scale and translate into products deployed in some of the world's most demanding industrial environments.