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.
Are you ready to revolutionize microbiology monitoring in factories? Spore Bio is seeking a ML Infrastructure Engineer with deep backend, infrastructure, and database expertise to join our software team. You'll design, build, and operate the core systems that our scientists and clients rely on every day, from data pipelines and APIs to cloud infrastructure and database architecture.
This is a hands-on individual contributor role. You'll have significant ownership over technical decisions and will work closely with a small, high-caliber team where your contributions have direct, visible impact.
Our machine learning models sit at the heart of Spore.Bio's technology. To unlock their full potential, we need robust, scalable, and production-ready infrastructure.
As an ML Infrastructure Engineer, you'll be responsible for designing and operating the platforms, tooling, and workflows that power our AI development lifecycle. You'll help bridge the gap between research and production, enabling our teams to train faster, experiment more efficiently, and deploy reliable models at scale.
Working alongside world-class experts in microbiology, optics, AI, and software engineering, you'll tackle challenges that few companies get to solve, bringing breakthrough scientific innovation into industrial environments around the world.
Develop and maintain deep learning infrastructure in the Machine Learning team
Architect relevant and coherent solutions for cloud R&D as well as on-edge deployments
Implement those solutions in a flexible, ever-changing environment
Be the owner of training, experiments and validation pipelines, and setup robust training infrastructure.
Participate in deployment of the machine learning models: ensure the deployed model works properly in production
Work closely with Microbiology, Optics and Software teams and implement processes to bolster ML collaboration
We believe in continuous learning and growth, so not all skills are mandatory.
Education/Background: Engineering or Masterʼs degree in Computer Science, Data Science or related fields
5+ years of experience implementing computer vision or deep learning pipelines
Expert in deep learning, PyTorch, distributed trainings and inference
Knowledge of cloud infrastructure, significant experience with at least one cloud provider AWS or GCP is a plus)
Experience with large scale computing environments Kubernetes, Slurm) and GPU scheduling.
Experience in refactoring and testing thoroughly Python code
Ability to manage communication across multidisciplinary teams (biology, optics, ML, etc.).
Core Data engineering know-how: SQL, data pipelines, labeling workflows, dataset versioning.
Get things done and high agency mindset
- 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.
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!
Discovery call (30 min) A conversation with someone from the software team to get to know each other. We'll discuss your background, motivations, and what you're looking for. It's also your chance to ask anything about Spore.Bio, the team, and the role.
Technical case study (take-home + 1 hr debrief) We'll send you a practical challenge that reflects the kind of problems you'd actually solve here. Think system design, data modeling, and building a small service. It's scoped to a few hours, not a weekend project. You'll then walk us through your approach with team members. We care about your reasoning and trade-offs, not trick questions or textbook algorithms.
Founders interview (1 hour) A conversation with our founders about vision, culture, and how we work together. This is as much for you as it is for us. We want you to have a clear picture of where Spore.Bio is headed and whether that excites you (or not).
Reference calls A quick chat with one or two people you've worked with before.
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!
Find more about us on our website and join us on this incredible journey!
