Overview In this role you will develop and deploy ML systems to enable planetary science from a Mars orbit mission. You'll work at the intersection of frontier AI and space science, building models that operate on spacecraft and fuse diverse data modalities. You'll own end-to-end problems from data understanding to deployment, collaborating with interdisciplinary teams to accelerate discovery. This is a high-visibility, autonomy-driven position with a strong impact on the mission architecture and science outcomes.
Compensation / Benefits- competitive salary and equity
- generous PTO and sick leave
- parential leave
- annual learning and development stipend
- opportunity to contribute to mission-critical aerospace projects
Responsibilities- Develop and deploy machine learning systems for the Mars orbit mission
- Build and optimize a real-time weather forecasting model to run on spacecraft at Mars
- Design and implement multi-modal data fusion to create coherent 3D representations
- Develop autonomous in situ science capabilities, including event detection and mission re-tasking
- Create the AI decision-making layer to close the loop and re-task the spacecraft autonomously
- End-to-end system development from dataset understanding to deployment and evaluation
- Communicate results effectively to scientists and engineers across teams
- Collaborate with the Interplanetary Sciences Team and Polymathic AI on research and deployment initiatives
Key requirements- PhD in a technical field and 3+ years of relevant industry experience
- Experience with transfer learning, domain adaptation or model fine-tuning in low-data settings
- Experience applying ML to physical datasets
- Working knowledge of multi-modal data fusion
- Ability to own problems end-to-end from data to deployment
- Willingness to collaborate with a diverse team of scientists and engineers
- Occasional travel (
- collaboration
- clear scientific communication
- creativity in combining ML principles with practical tools
- transfer learning
- domain adaptation
- model fine-tuning
