Computer Vision Engineer (AI/ML) - Bamboo Team

You'll join Bamboo's Computer Vision team in Paris as an integral, full-time member, reporting to the Head of AI. You'll work at the intersection of deep learning, geospatial analysis, and real-world solar construction, building CV systems that are deployed at scale on active job sites around the world. This is a role for someone who moves fast, digs deep, and wants their work to have a direct impact on the energy transition.

The Computer Vision team owns the full ML lifecycle for Bamboo: from problem framing and dataset curation, through model development and validation, to production deployment and continuous improvement.

We build in an AI-first way. AI coding agents, AI-assisted code review, and AI-driven testing and debugging are core parts of how our engineering team ships software day to day, not experimental side projects — and we're looking for engineers who already work this way and want to keep pushing how far it can go.

Beyond deep technical expertise, we're looking for someone who is genuinely excited about applying cutting-edge computer vision to one of the most impactful challenges of our time: accelerating the clean energy buildout. You'll work closely with engineering teams in Paris and our external development partners in Belgrade, Serbia.

What You'll Do

• Write clean, production-grade Python code across the full ML stack — data pipelines, model training, inference services, and evaluation frameworks
• Build, test, ship, and support production ML/CV features using AI-first and AI-native engineering workflows — AI coding agents, AI-assisted review, and AI-driven testing and debugging are default tools here, not optional extras
• Track and apply the latest advances in computer vision and deep learning, from foundation models to efficient inference architectures, to real-world construction challenges
• Design and run rigorous testing and validation protocols for ML-based products in challenging, real-world construction site conditions
• Partner closely with cross-functional engineering teams (frontend, backend, data, infra) and external development partners to ship integrated features
• Own the end-to-end ML lifecycle: design, train, evaluate, and deploy models that digitalize every phase of a solar plant, from development and design through construction and operations
• Serve as a technical bridge to users of developed tools, gathering field feedback, debugging edge cases, and closing the loop between model performance and real-world outcomes
• Contribute to team culture and cross-office cohesion, bridging the Paris team with engineering, product, and field operations teams worldwide