Machine Learning Engineer, Floodbase
AI & satellite flood tracking
Job no longer available
AI & satellite flood tracking
21-100 employees
Job no longer available
21-100 employees
Company mission
To enable all communities to prepare and respond to climate disasters by reducing the barriers to scientific information and capital.
Role
Who you are
- An intellectually curious and driven individual who is interested in working on innovative, impactful problems to address the climate crisis
- Bachelor’s in a quantitative discipline with 4+ years of industry experience or Master’s or PhD with 1-2+ years of industry experience
- Have demonstrated experience working in interdisciplinary teams solving complex problems that rarely have a clean, correct solution
- High coding proficiency in Python: can independently develop code and make and review contributions to a shared repository
- Familiar with open-source geospatial ecosystems (rasterio/gdal, shapely, geopandas, xarray/rioxarray, dask)
- Mastery of the fundamentals of scientific data analysis, statistics, and machine learning
- Have a proven track record (open source projects, Kaggle, publications, etc) of developing new models for innovative applications
- Keep up with state-of-the-art modeling techniques, like foundation models, and identify practical approaches for scalable solutions to environmental problems
- Prior experience with satellite imagery and/or geospatial modeling is a plus
What the job involves
- We are looking for an experienced Machine Learning Engineer to build algorithms to synthesize data from satellites, hydrologic models, and ground sensors into actionable insights. We produce flood data that informs emergency response and enables parametric flood insurance for governments, farmers, and businesses.
- You will take ownership of large projects, and your work will shape the full pipeline from training data selection to model training, validation, and output transformation and analysis. You will work with a team of scientists and engineers with expertise in remote sensing, hydrology, index insurance, climate, social vulnerability, and machine learning to build the next generation of tools to ensure financial protection from floods.
- We produce cutting-edge AI climate science, and you will play a large role in leading the edge of this field, with opportunities to publish in leading journals and present at top tech and science conferences. The role is remote, with core hours in EST or hybrid based in Brooklyn, NY
- Use your analytical expertise to derive robust insights from large structured and unstructured datasets of observations, hydrologic model outputs, and auxiliary records (stream gauges, water occurrence, …) that can be incorporated into the Floodbase parametric insurance product
- Example project: Automate the manual validation process of our historical flood data for individual areas of interest (AOIs) by finding robust rules leveraging multiple validation data sources
- Estimate risk of flooding and its associated uncertainty bounds informed by satellite observations for parametric insurance product design in collaboration with insurance market experts and product managers
- Example project: Find ways to add uncertainty estimates to our flood parametric product by sampling additional data points spatially around the AOIs or with statistical resampling methods like bootstrapping
- Utilize your proficiency in Machine Learning to advance the state of the art in flood detection from large datasets of observational data and models that can specifically inform the flood response needs of Floodbase customers
- Example project: Train a global flood segmentation model on Sentinel-2 data that improves on challenging urban scenes and inside mountain and cloud shadows
- Be a technical leader in the team and advocate for customer-centric product development based on time-bound scientific hypotheses-oriented experiments
- Manage, mentor, and recruit exceptional data scientists from a variety of backgrounds
- Visualize and explain work through presentations and notebooks
- Work closely with our team of machine learning engineers, research scientists, and software developers to translate rigorous science and research into robust products
Our take
As natural disasters increase in occurrence due to climate change, Floodbase is addressing the uneven preemption times of insurers and government bodies by mapping and tracking potential floods through satellite imagery. Floobase uses the data collected to influence insurance claims and help communities prepare and respond to oncoming floods.
Founded by Masters students at Yale University, Floodbase’s prototype was supported by Google and quickly gained interest from investors due to its convergence of social and financial adaptation goals. Backed by several major low carbon investment firms, Floodbase’s photography has been featured on the front cover of major publications and its technology has been used by the United Nations to help improve disaster response times.
With plenty of capital behind it, Floodbase has little in the way of competition and is using its technical capabilities to develop new types of flood insurance for vulnerable communities.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 6 rounds)
Feb 2025
$5m
EARLY VC
Jan 2023
$12m
SERIES A
Total funding: $37.6m
Company HQ
Downtown Brooklyn, NY
Leadership
Beth Tellman
(Co-Founder & Chief Scientist)Currently Assistant Professor at University of Arizona. Previously Postdoctoral Researcher at Columbia University and MA Environmental Science at Yale University.
Bessie Schwarz
(Co-Founder & CEO)Previously Strategist at Yale Program on Climate Change Communication, Research Affiliate at Data Pop Alliance and Field Doctor at Environment Colorado.
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