Computer Vision Engineer, Bamboo

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

Master's degree in Computer Science, Machine Learning, or a related field — or equivalent professional/research experience

Proven, hands-on experience building, testing, shipping, and supporting production B2B applications using AI-first or AI-native engineering workflows — proficiency with AI coding agents and AI-assisted development tools is expected, not a nice-to-have

2+ years of hands-on experience developing and deploying AI/ML models and pipelines (academic or industry)

Strong Python proficiency — you write clean, testable, well-structured code

Solid Computer Vision fundamentals and applied experience across detection, segmentation, classification, or related tasks

Deep learning framework experience: PyTorch and/or TensorFlow

Experience with data annotation tooling and labeling validation workflows

MLOps experience: experiment tracking, model versioning, deployment pipelines (e.g. MLflow, DVC, Docker, CI/CD)

Comfortable working remotely and collaborating asynchronously across time zones

Strong written and verbal communication in English (French is a plus)

Solid grasp of agile development practices and the full software product lifecycle

PhD in Computer Science, Computer Vision, or a related field

Experience with LLMs, Vision-Language Models, or Foundation Models applied to structured prediction or grounding tasks

Track record evaluating, adopting, or championing new AI-assisted engineering tools and practices within a team

Track record building robust ETL pipelines for large, evolving datasets

Experience with digital twin concepts — modeling and tracking physical assets and processes in software

Hands-on experience with GIS technologies (PostGIS, GDAL, geospatial data formats, coordinate systems)

Startup or scale-up experience, shipping new products in fast-moving, resource-constrained environments

Terabase offers the opportunity to work at the intersection of renewable energy, advanced software, robotics, and AI — using modern, leading-edge, AI-native engineering practices as the default way we build. You'll help build technology that directly accelerates the global transition to clean energy infrastructure at massive scale — and as an early member of the Bamboo CV team, you'll have outsized influence over how that product's computer vision capabilities are built from the ground up.