AI Engineer - Bioprocess data modeling @InSpek

Paris, France

Breega

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WHO ARE WE

InSpek uses optical microchip technology to sense multiple molecules, temperature, acidity, oxygenation, and more in real time, directly at the heart of biochemical reactions. Our sensors help produce medicines, food, and energy while reducing waste. We make sensors better, cheaper, and smaller!

Do you want to join a young, dynamic, ambitious, and VC-backed startup?

Then InSpek is the place for you!

WHAT WILL YOU BE DOING

As our A.I. Engineer for bioprocess data, you will work closely within the application team to develop robust, scalable machine learning models that extract actionable insights from complex biochemical and spectroscopic datasets. Your work will power the intelligence behind InSpek’s sensor solutions—delivering real-time, prebuilt models that customers can use out-of-the-box.

RESPONSABILITIES

Model Development & Data Science

  • Design, train, and evaluate machine learning models (including classical ML and deep learning) to interpret large-scale time-series and spectroscopic datasets.
  • Develop in collaboration with our senior chemometrician preprocessing pipelines (noise reduction, normalization, dimensionality reduction, etc.) tailored for bioprocess signals.
  • Optimize algorithms for signal interpretation, feature extraction, and classification/regression tasks.
  • Validate model robustness using cross-validation, hyperparameter tuning, and uncertainty quantification.

Data Infrastructure & Integration

  • Build modular, scalable model pipelines to enable rapid experimentation and deployment.
  • Collaborate with firmware and software teams to integrate models into embedded systems or cloud platforms.
  • Support the creation of intuitive, customer-ready solutions for end-users to access model outputs.

Analytics & Documentation

  • Create and maintain clear documentation of model development, experiments, and performance metrics.
  • Work on statistical reports and dashboards to support product development and regulatory compliance.


COMPETENCIES / PROFIL

You’re a hands-on problem-solver who thrives in data-rich environments. You enjoy transforming complex information into elegant, high-impact models. You're eager to contribute to both the technical and strategic growth of a deep-tech company.

  • MSc or PhD (or equivalent experience) in Artificial intelligence, machine learning, data science, or a related field
  • Solid experience with Python and its scientific ecosystem (NumPy, pandas, scikit-learn, PyTorch/TensorFlow).
  • Proficient in building and validating machine learning models (e.g., SVMs, neural networks, ensemble methods).
  • Very good communication skills, both in articulating technical concepts to clients and collaborating with cross-functional teams
  • Effective project management and organizational skills to coordinate with various stakeholders and ensure timely delivery of project outcomes
  • Proficiency in English, French is a plus
  • Experience working with spectroscopic data is a plus
  • Good comprehension of bioproduction and pharmaceutical processes is a plus

BENEFITS

💼 Health and life insurance (100%)

🍽️ Meal vouchers

🏃🏼 Gymlib account (access to gyms & sports)

📈 Employee stock options (BSPCE)

🏡 Flexible remote work policy

🎉 Regular social events

💥 Growth opportunities with potential for leadership roles

🌟 Inclusive culture

🚀 Unique opportunity to be an early employee at an innovative startup

InSpek’s offices & laboratories are located at DocCity Suresnes, in the western Paris region.

We welcome candidates from all backgrounds and experiences to apply, even if you don’t tick all the requirements.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Classification Deep Learning Machine Learning ML models NumPy Pandas Pharma PhD Pipelines Python PyTorch Scikit-learn Statistics TensorFlow

Perks/benefits: Career development Equity / stock options Flex hours Health care Startup environment Team events

Region: Europe
Country: France

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