Rainmaker Fellow, Machine Learning (Science)

TL;DR

hirify.global Fellow, Machine Learning (Science): Conducting applied research on atmospheric datasets to improve precipitation-enhancement models with an accent on sensor data, sequence modeling, and uncertainty quantification. Focus on building reproducible baselines, evaluating model performance on weather events, and delivering durable research artifacts.

Location: Must be based in El Segundo, CA for on-site work

Compensation: $8,000 per month

Company

hirify.global is a science-driven organization pioneering modern cloud-seeding systems to improve water availability and address severe-weather challenges.

What you will do

• Translate scientific or operational questions into measurable machine learning problems.
• Build and improve training and validation datasets using real sensor and operational data.
• Establish reproducible baselines and train models using held-out weather events.
• Quantify model calibration, uncertainty, and sensitivity to biased data.
• Collaborate with atmospheric scientists to define physical constraints and success criteria.
• Produce clear documentation and present results to technical leadership.

Requirements

• Must be available for full-time, on-site work in El Segundo, CA.
• Current student (undergraduate, master's, or PhD), postdoctoral researcher, or recent graduate.
• Strong Python programming ability and experience with modern ML frameworks.
• Ability to independently build, test, and debug technical work.
• Strong quantitative reasoning and experimental design skills.
• Clear written and verbal communication.

Nice to have

• Background in meteorology, remote sensing, robotics, or scientific computing.
• Experience with sequence modeling, computer vision, or data assimilation.
• Knowledge of weather systems and atmospheric science.

Culture & Benefits

• Full health coverage including medical, dental, and vision insurance.
• Lunch provided daily when working in-office.
• Fully stocked kitchenette and free EV charging at headquarters.
• Opportunity to work on high-impact research with expert mentors.