Machine Learning Engineer – Computer Vision / Applied Research

Why to join our ML team?

• Join a Machine Learning team that sits at the core of Inarix’s technology, powering every product we build.

• Unique data in a niche domain — you’ll work with proprietary, high-quality datasets rarely found elsewhere, enabling truly original modeling challenges.

• The opportunity to build state-of-the-art AI systems that have tangible, real-world applications, bridging research and production, for which you’ll have a strong ownership.

• A research-driven, engineering-minded ML team that values autonomy, technical depth, and meaningful results.

• Access to solid computing infrastructure and the tools you need to iterate fast and experiment effectively.

• A remote-first culture with access to our offices in Paris.

About the role

We’re looking for a Machine Learning Engineer with a passion for Computer Vision and Applied Research to join our ML team developing AI models for cereal analysis.

At Inarix, you’ll be at the core of our technology. Over the past years, and leveraging the latest advances in deep learning, we’ve built a unique set of techniques, tools, and models to transform images of grains into reliable, scalable insights. Our technology, powered by a domain-specific grain foundation model, can already identify cereal varieties (sub-species of barley, wheat, corn, etc.) at the grain level, estimate protein or moisture content, and detect broken or other damages in grains — all from simple images.

You’ll work end-to-end: from data acquisition and labeling pipelines, to model design, training, deployment, and monitoring. A significant part of your time will be dedicated to applied research, optimization, and system design, with the goal of improving both model performance and product robustness. You’ll help design, train, and deploy models that power real products — combining scientific rigor with engineering pragmatism, with access to large proprietary datasets, advanced experimentation tools, and a team experienced in research and large-scale ML deployment.

Your work will directly impact product quality and model scalability, while shaping future product lines and use cases. You'll work in an environment that values both deep research exploration and efficient, production-oriented AI — tackling niche yet high-impact applications where much remains to be discovered, including the development of foundation models built on our grain datasets. This involves addressing challenges in multi-domain generalization, product-specific research, edge cases, and everything needed to make our models truly ready for production use.

Your impact and responsibilities

• Design, build, train, evaluate, and deploy computer vision models ready for production use, through iterative experimentation, focusing on solid metrics and reproducible results.

• Contribute to the development of foundation models specifically trained on our large-scale grain datasets, advancing our ability to generalize across products and domains.

• Collaborate across teams to translate high-level needs into clear ML objectives and measurable performance criteria.

• For novel use cases, explore and validate new modeling strategies grounded in both academic insights and empirical testing.

• Ensure production readiness through efficient pipelines, robust post-processing, and well-tested integrations.

• Monitor and improve deployed models based on performance data and feedback from real-world usage.

• Contribute to our ML core: shared tools, model evaluation frameworks, production inference system, and team-wide best practices.

• Spend time to exploring new ideas — testing emerging methods, experimenting with alternative representations, and challenging existing assumptions to continuously improve our modeling capabilities.