Senior Machine Learning Scientist, Climate & Hydrology

The role

The Senior Machine Learning Scientist will lead scientific direction and machine learning development for hydrology-aware climate modeling. This role works across science, ML, engineering, and data teams to build next-generation prediction systems.

What you will do

• Lead scientific and technical efforts at the intersection of hydrology, climate science, and machine learning.
• Define research priorities, modeling directions, and evaluation strategies for prediction systems.
• Develop and improve ML-based modeling approaches informed by physical and Earth system science.
• Work with large-scale climate, weather, hydrology, and remote sensing datasets.
• Build and oversee reproducible workflows for data processing, model training, benchmarking, and validation.
• Collaborate with research, engineering, and data teams to translate scientific goals into technical execution.
• Guide assessment of model performance, uncertainty, and scientific robustness.
• Communicate findings through internal reviews, external collaborations, publications, and technical presentations.
• Shape the broader scientific roadmap and contribute to team growth and cross-functional leadership.

Required qualifications

• PhD in machine learning, computational science, Earth science, atmospheric science, hydrology, AI, computer science, or a related quantitative discipline.
• 5+ years of postdoctoral, industry, or applied research experience in climate ML, weather ML, hydrologic modeling, Earth system modeling, or a closely related field.
• Demonstrated experience with ML-accelerated weather, climate, or hydrology models.
• Strong publication track record in the area.
• Experience working with large climate datasets, including reanalysis products, remote sensing datasets, observational datasets, and model output.
• Experience with the computational infrastructure required to manage, preprocess, and train on large-scale climate datasets.
• Strong programming skills in Python.
• Experience with modern ML frameworks such as PyTorch.
• Ability to design rigorous evaluation frameworks, performance metrics, and benchmarking approaches for environmental prediction systems.
• Strong technical writing and communication skills.
• Ability to work independently in fast-paced, ambiguous environments while collaborating effectively across disciplines.

Nice to have

• Experience in the AWS ecosystem.
• Background in scientific ML, spatiotemporal modeling, data assimilation, hybrid physics-ML methods, or related approaches.
• Experience leading cross-functional scientific efforts, mentoring researchers, or helping define research roadmaps.

Benefits

• Healthcare coverage
• Annual incentive program
• Retirement benefits

About the company

Flagship Pioneering is a bioplatform innovation company that invents and builds companies that change the world. It unites innovation, company creation, and capital investment to advance science and technology.