Senior Machine Learning Scientist, Climate & Hydrology

Flagship Pioneering; Cambridge (MA); Hybrid; USD 168,000 - 231,000; Full time

Benefits offered by this job

Healthcare coverage

Annual incentive programs

Retirement benefits

Job summary

Flagship Pioneering in Cambridge, MA, is seeking a Senior Machine Learning Scientist specialized in climate and hydrology. This role involves leading the development for hydrology-aware climate modeling and integrating modern ML methods into environmental predictions.

The ideal candidate has a PhD, 5+ years of experience in climate ML, and strong programming skills in Python. You will contribute to groundbreaking systems that enhance scientific accuracy and predictive capabilities.

Qualifications

• 5+ years of experience in climate ML, weather ML, or hydrologic modeling.
• Strong publication track record in machine learning applications.
• Experience with large climate datasets and technical infrastructure.

Responsibilities

• Lead scientific and technical efforts in climate ML and hydrology.
• Define research priorities and modeling strategies.
• Collaborate with teams to translate goals into technical execution.

Skills

Machine learning

Computational science

Python

Spatiotemporal modeling

Data assimilation

Education

PhD in machine learning or related fields

Tools

PyTorch

AWS

Job description

THE ROLE

We are seeking a Senior Machine Learning Scientist, Climate and Hydrology to lead the scientific direction and machine learning development for hydrology‑aware climate modeling within our broader environmental modeling platform. This role sits at the intersection of hydrology, weather and climate science, and large‑scale machine learning. The Sr. Scientist will help shape how hydrologic process understanding, climate data, and modern ML methods are brought together in next‑generation prediction systems, with emphasis on scientifically grounded model development and evaluation.

KEY RESPONSIBILITIES

• Lead scientific and technical efforts at the intersection of hydrology, climate science, and machine learning.
• Help define research priorities, modeling directions, and evaluation strategies for next‑generation climate and environmental prediction systems.
• Contribute to the development and improvement of ML‑based modeling approaches informed by physical and Earth system science.
• Work with large‑scale climate, weather, hydrology, and remote sensing datasets to support model development and scientific analysis.
• Build and oversee reproducible workflows for data processing, model training, benchmarking, and validation.
• Collaborate closely with research, engineering, and data teams to translate scientific goals into scalable technical execution.
• Guide assessment of model performance, uncertainty, and scientific robustness across a range of environmental conditions and applications.
• Communicate findings through internal reviews, external collaborations, publications, and technical presentations.
• Help shape the broader scientific roadmap and contribute to team growth and cross‑functional leadership.

PROFESSIONAL EXPERIENCE & 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, with a 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, preferably in the AWS ecosystem.
• Strong programming skills in Python and experience with modern ML frameworks such as PyTorch.
• Background in scientific ML, spatiotemporal modeling, data assimilation, hybrid physics‑ML methods, or related approaches is strongly preferred.
• Ability to design rigorous evaluation frameworks, performance metrics, and benchmarking approaches for environmental prediction systems.
• Strong technical writing and communication skills, including reports, presentations, and peer‑reviewed publications.
• Demonstrated ability to work independently in fast‑paced, ambiguous environments while collaborating effectively across disciplines.
• Experience leading cross‑functional scientific efforts, mentoring researchers, or helping define research roadmaps is preferred.

LOCATION

Cambridge, MA or Boulder, CO (some travel to Cambridge, MA based headquarters if working from Colorado).

BENEFITS & COMPENSATION

Salary ranges for this role are $127,000 - $205,900 (Colorado) and $168,000 - $231,000 (Massachusetts). Compensation will depend on factors such as qualifications, skills, competencies, and experience. The company offers healthcare coverage, annual incentive programs, retirement benefits, and a broad range of other benefits. Compensation and benefits information is based on the company’s estimate as of the date of publication and may be modified in the future.

EEO STATEMENT

We are an equal‑opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in the company.