Deep Learning Scientist — Computer Vision for Microbiology

Spore; Paris; Hybride; EUR 60 000 - 80 000; Plein temps

Résumé du poste

An innovative startup in microbiology is seeking a Deep Learning Scientist specialized in Computer Vision to design advanced models for interpreting biophotonic data. This role involves collaboration with biologists and physicists to derive insights through AI. Ideal candidates will have robust experience in deep learning and computer vision, particularly with tools like PyTorch. The position offers flexible remote work options and numerous perks like health insurance and a gym subscription, promoting a collaborative work environment.

Prestations

Budget for remote work equipment

Gymlib subscription

Premium health insurance

Swile card for meals

Frequent team events

Qualifications

• Strong foundations in Deep Learning theory and model architectures.
• Proven experience in Computer Vision, such as segmentation and detection.
• Experience in translational research applications of AI.

Responsabilités

• Develop, train, and optimize deep learning models for biological data.
• Implement state-of-the-art methods in real-world biomedical contexts.
• Collaborate to design experiments and validate biological relevance.

Connaissances

Deep Learning theory

Computer Vision

Translational research

PyTorch

Clean code practices

Outils

PyTorch

Lightning

TorchVision

HuggingFace

Description du poste

About us

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.

And now, we’re entering the next chapter.

We’re building a team of exceptional researchers, engineers, and scientists who will bring this project out of stealth mode and push the boundaries of biophotonics, genomics, and AI. If you want to work at the frontier of AMR research, help shape open scientific infrastructure, and contribute to a global effort backed by Google, we’d love to meet you.

About the role

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.

Main Responsibilities

• 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.

About you

Required qualifications/ experience :

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).

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

• 30-min call with the Hiring Manager

• 45-min personality interview with two team members

• 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!