Senior AI/ML Scientist — Mars Autonomy & Science

Relativity Space; Long Beach (CA); On-site; USD 154,000 - 211,000; Full time

Benefits offered by this job

Competitive salary

Equity

Generous PTO and sick leave

Parental leave

Annual learning and development stipend

Job summary

Relativity Space in Long Beach, CA is seeking an AI/ML Scientist to develop machine learning systems aimed at unlocking new science from our 2028 Mars orbital mission. The role involves building AI models and enhancing atmospheric modeling for Mars, integrating diverse datasets to produce coherent insights. This is a unique opportunity to collaborate with a vibrant interdisciplinary team while contributing to groundbreaking planetary research.

The ideal candidate should hold a PhD in a relevant field, possess experience in machine learning applications, and be passionate about planetary science.

Qualifications

• 3+ years of relevant industry experience.
• Demonstrated experience in low-data or out-of-distribution settings.
• Excited to collaborate with scientists and engineers.

Responsibilities

• Develop and deploy machine learning systems for Mars orbital mission.
• Enhance Mars atmospheric modeling and weather forecasting.
• Build methods for reconstructing 3D representations from datasets.

Skills

Transfer learning

Domain adaptation

Machine learning application in physical datasets

Multi-modal data fusion

Problem ownership end-to-end

Education

PhD in machine learning, computer science, physics, or related field

Job description

Relativity Space in Long Beach, CA is seeking an AI/ML Scientist to develop machine learning systems aimed at unlocking new science from our 2028 Mars orbital mission. The role involves building AI models and enhancing atmospheric modeling for Mars, integrating diverse datasets to produce coherent insights. This is a unique opportunity to collaborate with a vibrant interdisciplinary team while contributing to groundbreaking planetary research.

The ideal candidate should hold a PhD in a relevant field, possess experience in machine learning applications, and be passionate about planetary science.