AI Climate Modeler — Multidecadal Forecasts

Allen Institute for Artificial Intelligence; Seattle (WA); On-site; USD 150,000 - 170,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k)

Commuting stipend

Wellbeing stipend

Vacation days

Holidays

Annual bonus

Job summary

Allen Institute for Artificial Intelligence seeks a Young Investigator for a three-year project to develop an AI-powered climate model blending physics with ML. You will lead design and evaluation of NeuralGCM+ training cases using historical data and physics-based outputs.

You''ll collaborate with a small team, mentor interns, present results at AI and climate conferences, and contribute open‑source code amid a collaborative, Seattle-based environment.

Qualifications

• Substantial experience building and deploying a relevant ML application in a practical or academic research setting.
• Fluent in Python and collaborative coding practices.
• PhD with at least one accepted conference paper or peer‑reviewed first‑authored publication making extensive use of ML.

Responsibilities

• Select, design and evaluate NeuralGCM+ training and testing cases, using both historical data and customized physics-based climate model outputs.
• Conceive and implement NeuralGCM+ model improvements that increase generalizability to unseen climates and improve coupling between earth system components.
• Present results at major AI and climate modeling conferences and in peer‑reviewed publications.
• Open-source code development as part of a tightly connected team, including daily meetings, code review, design documents and interaction with external collaborators.
• Mentor interns as appropriate.

Skills

Python

ML

Education

PhD in computer or computational science / atmospheric science

Tools

JAX

Job description

Allen Institute for Artificial Intelligence seeks a Young Investigator for a three-year project to develop an AI-powered climate model blending physics with ML. You will lead design and evaluation of NeuralGCM+ training cases using historical data and physics-based outputs.

You''ll collaborate with a small team, mentor interns, present results at AI and climate conferences, and contribute open‑source code amid a collaborative, Seattle-based environment.