About Sylvera Sylvera empowers organizations to make informed investments in carbon and commodity markets. Our independent assessments of carbon project quality, market pricing, and supply signals, alongside our geospatial and carbon intensity data, provide clients with the vital insights needed for impactful climate action.Our diverse team of over 130 scientists, engineers, and market analysts operates across major cities including London, New York, São Paulo, Singapore, and Tokyo. We specialize in market intelligence, geospatial analytics, multi-scale lidar research, and policy analysis, partnering with governments to enhance transparency and rigor in carbon markets.With backing from over $96 million in investment from prominent firms like Fidelity, Balderton Capital, Index Ventures, and Insight Partners, we are trusted by Fortune 500 companies and major financial institutions globally.If you are passionate about climate science, enjoy tackling complex challenges, and wish to work with a dedicated team committed to our mission, we invite you to explore this opportunity.Role Overview We are seeking a dedicated Applied Scientist – Forest Lidar & 3D ML to join our Earth Analytics (EA) team.Your primary focus will be to address a significant research challenge in a high-impact commercial context: the automation of tree segmentation from intricate terrestrial laser scanning (TLS) point clouds. Your work will be pivotal in enhancing Sylvera’s innovative Biomass Atlas product, which is increasingly utilized for carbon accounting within carbon markets. You will gain exclusive access to a premier ground-truth, labeled dataset of 3D forest point clouds sourced from global forests.Key Responsibilities:Designing, training, and implementing advanced 3D deep learning models (e.g., sparse convolutions, PointNet, TreeLearn, or similar architectures) for automating tree instance segmentation and Quantitative Structure Model (QSM) generation.Converting experimental machine learning research into reliable, reproducible code, collaborating closely with our production engineering team to deploy models at scale.
Apr 1, 2026