Operational Weather ML Researcher — Stock Options & PTO

Front Door Defense; El Segundo (CA); On-site; USD 160,000 - 220,000; Full time

Benefits offered by this job

Stock options

401(k)

Health coverage

Relocation assistance

Unlimited PTO

Parental leave

Lunch provided

EV charging

Job summary

Rainmaker is hiring its first dedicated Machine Learning Researcher to establish how the company uses machine learning across the organization: identifying valuable problems, deciding which are ML-ready, building working models, and partnering with engineers and domain experts to turn research into operational systems.

You will not inherit a fixed model roadmap; the role covers forecasting supercooled liquid water and cloud-seeding opportunities, multimodal state estimation, and learning from

Qualifications

• Exceptional ability in machine learning research and engineering.
• Strong command of modern machine‑learning methods and practical experience training, evaluating, and debugging models.
• Strong Python skills and experience with a modern ML framework such as PyTorch, JAX, or an equivalent system.

Responsibilities

• Assess potential ML projects across Rainmaker and prioritize them by operational value, data readiness, technical tractability, and time to useful results.
• Deliver an operationally useful model or prototype within your first three months rather than spending a quarter exclusively on infrastructure or roadmap development.
• Build models for forecasting, nowcasting, retrievals, multimodal atmospheric‑state estimation, simulation, intervention analysis, and other scientific or operational applications.
• Develop methods for forecasting the occurrence, location, amount, and persistence of supercooled liquid water at scales relevant to cloud‑seeding operations.
• Combine public NWP, radar, satellite, microwave‑sounder, aircraft, UAS, sounding, surface, and in‑situ observations.
• Build datasets, labels, baselines, evaluation metrics, and validation procedures for variables that public systems do not observe or optimize well.
• Establish honest experimental comparisons and characterize calibration, uncertainty, generalization, and failure modes.
• Work closely with meteorologists and atmospheric scientists to define targets, physical constraints, useful priors, and ground truth.
• Write research‑quality software and build prototypes that software engineers can help productionize when an approach proves valuable.
• Use Rainmaker's compute budget deliberately, scaling experiments only when the problem, data, and baseline justify it.
• Help Rainmaker learn from every operation, field campaign, new sensor, and intervention.
• Communicate results and limitations clearly to scientists, engineers, operators, and company leadership.

Skills

Python programming

ML research

Model evaluation

Multimodal data handling

Tools

PyTorch

JAX

Job description

Rainmaker is hiring its first dedicated Machine Learning Researcher to establish how the company uses machine learning across the organization: identifying valuable problems, deciding which are ML-ready, building working models, and partnering with engineers and domain experts to turn research into operational systems.

You will not inherit a fixed model roadmap; the role covers forecasting supercooled liquid water and cloud-seeding opportunities, multimodal state estimation, and learning from