Deep Learning Scientist - Computer Vision for Microbiology

As a Deep Learning Scientist specialized in Computer Vision, you will design and implement state-of-the-art models to extract and interpret complex patterns from biophotonic and microscopic data.

You will collaborate closely with microbiologists and physicists to translate optical signals and biological phenomena into actionable insights through AI., * Develop, train, and optimize deep learning models (CNNs, Vision Transformers, self-supervised and generative approaches) for the analysis of biological and optical imaging data.

• Implement state-of-the-art methods from the latest literature and adapt them to real-world biomedical contexts.
• Translate research concepts into robust, scalable, and interpretable models ready for translational deployment.
• Collaborate with the biophotonics and microbiology teams to design experiments, define learning objectives, and validate biological relevance.
• Ensure good coding practices (modular design, documentation, version control, reproducibility).
• Contribute to scientific publications, conferences, and patents showcasing advances at the intersection of AI and microbiology., 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!, * A 1 hour technical case study followed by a debrief with team members
• 1 hour Founders interview
• Reference calls

You might also be invited to meet other team members at the office for a lab visit and a coffee !

This is a unique opportunity for someone who thrives on curiosity and has a genuine passion for technology. If you enjoy taking on challenges and solving complex problems, this role will provide the perfect environment for growth and impact. The ideal candidate is someone who is self-driven, eager to learn, and excited to contribute to shaping the future of microbiology monitoring. Join our innovative and dynamic team, and let's make a difference together! We look forward to meeting you!

We value curiosity, initiative, and a growth mindset: not every box needs to be ticked to apply. * Strong foundations in Deep Learning theory and model architectures (CNNs, ViTs, Diffusion models, etc.).

• Proven experience in Computer Vision (segmentation, detection, contrastive or self-supervised learning).
• Experience in translational research - bringing AI from proof-of-concept to real-world biomedical use.
• Mastery of PyTorch and associated ecosystems (Lightning, TorchVision, HuggingFace).
• Familiarity with data preprocessing pipelines, model interpretability, and performance evaluation.
• (Bonus) Experience with clean code, testing, and deployment best practices (MLOps mindset).

At Spore.Bio, we're reinventing how microbiology is done in industrial and clinical settings. After months spent inside factories and labs, we saw firsthand how slow and constrained traditional microbiological workflows still are. So we built a new paradigm using advanced optics and deep learning to deliver results in seconds instead of days. Today, we're taking this mission a step further. We created Spore.Labs, our fundamental research division dedicated to one of the biggest global health challenges starting with antimicrobial resistance (AMR). With the support of the Google.org AI for Science Initiative, Spore.Labs is launching an open-source program to reduce AMR diagnostic time from days to minutes enabling rapid identification of resistance genes and promoting targeted, responsible antibiotic use.