Computer Vision Engineer, Bamboo

Terabase Energy

6d•Remote

About The Position

At Terabase Energy, we believe that digitalization and automation will drive the next wave of innovation and cost reduction in large-scale solar. We work alongside project developers, owners, and engineering & construction firms to support the design, optimization, and construction of huge solar projects around the world. Our team is a blend of solar-industry veterans and newcomers, thought-leaders, dreamers, software, electrical and mechanical engineers, coders, product managers, project managers, and sales and marketing professionals. Terabase Energy is a well-funded scale-up headquartered in Berkeley, California, with several other offices around the world, including our growing Paris R&D hub. Alongside Construct, our flagship B2B SaaS construction management and quality control platform that has supported 16+ GW of projects from leading owners and EPCs, we're building Bamboo: a newer, fast-growing product line extending Terabase's AI and automation capabilities into new parts of the solar EPC lifecycle. The Computer Vision Engineer will join Bamboo's Computer Vision team in Paris as an integral, full-time member, reporting to the Head of AI. This role is 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. The team builds in an AI-first way, utilizing AI coding agents, AI-assisted code review, and AI-driven testing and debugging as core parts of how the engineering team ships software. Beyond deep technical expertise, the role requires someone genuinely excited about applying cutting-edge computer vision to accelerate the clean energy buildout. The engineer will work closely with engineering teams in Paris and external development partners in Belgrade, Serbia.

Requirements

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

Nice To Haves

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

Responsibilities

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