Rainmaker Fellow, Machine Learning

About the role#

The Rainmaker Machine Learning Fellowship is a paid, full-time research appointment for undergraduate and graduate students, postdoctoral researchers, and recent graduates. You will join the R&D team to work on a scoped machine learning project. You will take responsibility for a specific workstream while contributing to the broader team's research and technical decisions. Projects are defined in collaboration with a research mentor based on team needs and your background. This is a three-to-six-month appointment.

What you'll do#

• Translate a scientific or operational question into a measurable ML problem.
• Build or improve the training and validation dataset needed for the project.
• Establish simple, reproducible baselines before introducing more complex models.
• Train, evaluate, and debug models using held-out weather events or conditions.
• Work with atmospheric scientists to define targets, physical constraints, and operational success criteria.
• Produce clear, reusable code and documentation.
• Present your results to scientists, engineers, and technical leadership.
• Deliver a final artifact such as a benchmark dataset, model, prototype, or research paper.

What you'll need#

• Current enrollment in or recent completion of a degree in Computer Science, Data Science, Mathematics, Physics, Statistics, or Engineering.
• Strong Python programming ability and experience with a modern ML framework.
• Strong quantitative reasoning and the ability to design credible experiments.
• Ability to make progress on ambiguous research problems.
• Clear written and verbal communication skills.
• Interest in working with noisy, sparse, or physical data.

Location & details#

• Location: El Segundo, California.
• Modality: Full-time, on-site.
• Compensation: $8,000 per month.
• Benefits: Full health coverage (medical, dental, and vision), lunch provided when in-office, and free EV charging at headquarters.
• Applications are accepted on a rolling basis.