ML Fellow: Weather Data Science & Forecasting

Blackwing; El Segundo, Northern (CA, KY); Hybrid; USD 82,000 - 110,000; Full time

Benefits offered by this job

Full health coverage (medical, dental,

vision insurance)

Lunch provided & kitchenette

Free EV charging at HQ

Job summary

Rainmaker invites applications for a paid, full-time Machine Learning Fellowship based on-site in El Segundo. The program targets exceptional students, postdocs, and early-career researchers to work on a scoped ML project with mentorship and collaboration from Rainmaker's R&D team.

You will translate questions into ML problems, build datasets, establish baselines, and train and evaluate models using real sensor data.

Qualifications

• Current undergraduate, master's, or PhD students; postdoctoral researchers; recent graduates; and other early-career researchers are all eligible.
• Strong Python programming ability and experience with a modern ML framework.
• Evidence that you can independently build, test, and debug technical work.
• Strong quantitative reasoning and an ability to design credible experiments.
• Interest in noisy, sparse, multimodal, spatial, temporal, or physical data.
• Ability to make progress on ambiguous research problems while incorporating mentor feedback.
• Clear written and verbal communication.
• Availability for full-time, on-site work in El Segundo for the agreed appointment.

Responsibilities

• 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, regions, or operating conditions.
• Quantify calibration, uncertainty, generalization, failure modes, and sensitivity to missing or biased data.
• Work closely with atmospheric scientists to define useful targets, ground truth, physical constraints, and operational success criteria.
• Produce clear, reusable code and documentation.
• Present your results to Rainmaker's scientists, engineers, operators, and technical leadership.
• Deliver a final artifact such as a benchmark dataset, model, prototype product, evaluation report, or research paper.

Skills

Independent work

Quantitative reasoning

Clear communication

Problem solving

Mentor feedback adaptation

Education

Undergraduate or graduate student status

Tools

Python

ML framework

Job description

Rainmaker invites applications for a paid, full-time Machine Learning Fellowship based on-site in El Segundo. The program targets exceptional students, postdocs, and early-career researchers to work on a scoped ML project with mentorship and collaboration from Rainmaker's R&D team.

You will translate questions into ML problems, build datasets, establish baselines, and train and evaluate models using real sensor data.