SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Terabase Energy is building Bamboo, an AI and automation product line extending their capabilities into new parts of the solar EPC (engineering, procurement, construction) lifecycle. You'll join the Computer Vision team in Paris as a full-time engineer reporting to the Head of AI, working at the intersection of deep learning, geospatial analysis, and real-world solar construction.
The Computer Vision team owns the full ML lifecycle for Bamboo: problem framing, dataset curation, model development and validation, production deployment, and continuous improvement. The company emphasizes AI-first engineering practices—AI coding agents, AI-assisted code review, and AI-driven testing are core to how the engineering team ships software daily.
You'll write production-grade Python code across the full ML stack (data pipelines, model training, inference services, evaluation frameworks). You'll build, test, ship, and support production ML/CV features using AI-native workflows. You'll track and apply the latest advances in computer vision and deep learning to real-world construction challenges, design rigorous testing and validation protocols for ML products in challenging field conditions, and partner with cross-functional teams (frontend, backend, data, infra) and external development partners in Belgrade, Serbia.
You'll own the end-to-end ML lifecycle: designing, training, evaluating, and deploying models that digitalize every phase of a solar plant from development through operations. You'll serve as a technical bridge to users, gathering field feedback, debugging edge cases, and closing the loop between model performance and real-world outcomes. You'll also contribute to team culture and cross-office cohesion.
Terabase is a well-funded scale-up headquartered in Berkeley with offices worldwide, including a growing Paris R&D hub. Their flagship product, Construct, is a B2B SaaS construction management and quality control platform that has supported 16+ GW of projects from leading owners and EPCs.
REQUIREMENTS:
- Master's degree in Computer Science, Machine Learning, or 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 optional
- 2+ years of hands-on experience developing and deploying AI/ML models and pipelines (academic or industry)
- Strong Python proficiency with 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 HAVE:
- PhD in Computer Science, Computer Vision, or 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
- 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
