ML Scientist

About Carbon Mapper

Carbon Mapper is a pioneering non-profit organization headquartered in Pasadena, California, dedicated to combating climate change through innovative remote sensing technology. Our mission is to facilitate greenhouse gas emission reductions by providing accessible, accurate, and actionable data on methane and carbon dioxide emissions. We leverage a constellation of satellite-based sensors to detect, locate, and quantify emissions at the facility level, ensuring that data is publicly available on our Carbon Mapper Data Portal for non-commercial use. This transparency empowers policymakers, environmental organizations, and stakeholders to prioritize mitigation efforts effectively. In addition to data collection, Carbon Mapper collaborates with diverse partners to address data gaps, advance scientific research, and promote educational initiatives globally. Our work aims to catalyze meaningful climate action by transforming complex satellite data into insightful information that drives emissions reductions and supports sustainable development goals.

About The Role: ML Scientist

We are seeking a highly skilled ML Scientist to join our team and contribute to the development of next-generation machine learning methodologies tailored for Earth science and remote sensing applications. This role involves designing, implementing, and refining algorithms that enhance methane and carbon dioxide retrieval, plume detection, source attribution, and emissions rate quantification. The successful candidate will process and analyze large-scale geospatial datasets, evaluate model performance across diverse environments, and interpret model sensitivities to improve accuracy and robustness. Collaboration with research scientists and engineers will be essential to update and optimize models, ensuring continuous improvement of our data pipelines. The role offers an exciting opportunity to apply advanced machine learning techniques to real-world climate challenges, ultimately supporting global emissions monitoring efforts and climate mitigation strategies.

Qualifications

• Bachelor’s degree in environmental science, physical science, mathematics, geoscience, engineering, computer science, or a related field, or equivalent practical experience.
• Experience with machine learning libraries such as PyTorch or TensorFlow.
• Proficiency in processing and analyzing large-scale geospatial or remote sensing datasets.
• Strong communication skills and ability to collaborate effectively within interdisciplinary teams.
• Ability to manage multiple priorities in a dynamic, evolving work environment.

Nice-to-Have Skills

• Master’s or Ph.D. in a related field.
• Experience maintaining production or operational machine learning systems.
• Experience applying object detection or classification methods to satellite or remote sensing data.
• Proficiency in exploratory data analysis to enhance training datasets and model performance.
• Record of research publications, technical reports, or contributions to open-source projects.
• Familiarity with cloud computing platforms such as AWS.
• Interest in climate science, emissions monitoring, or Earth science applications.

Responsibilities

• Develop and adapt algorithms for methane and carbon dioxide retrieval, plume detection, source attribution, and emissions rate quantification.
• Process, clean, and analyze large-scale geospatial and remote sensing datasets to support model development.
• Evaluate model performance across different regions, environments, and datasets to identify and address performance variations.
• Assess model sensitivity and interpretability to ensure reliability and transparency of results.
• Maintain and update training datasets used for algorithm development and benchmarking purposes.
• Collaborate closely with research scientists and engineering teams to deploy and release improved model versions.
• Contribute to scientific publications, technical reports, and documentation related to machine learning models and findings.

Benefits

• Comprehensive health coverage including medical, dental, and vision plans.
• Generous paid time off and holiday leave policies.
• Opportunities for professional development and continuous learning.
• Flexible work arrangements, including virtual office options.
• Participation in impactful projects addressing climate change and environmental sustainability.
• A collaborative and inclusive work environment that values diversity and innovation.

Key skills/competency

• Machine Learning
• Remote Sensing
• Geospatial Data
• Python Programming
• PyTorch / TensorFlow
• Climate Science
• Algorithm Development
• Data Analysis
• Methane Emissions
• CO2 Quantification