Planet→
Intern, AI/ML Engineer at Planet in San Francisco, CA
InternshipHybridFull-timeSan Francisco, CA$73k–$125k/yr
Skills
ai/ml algorithmspythongeospatial analyticsnumerical computingdata processingcuriosity
Job Description
Summary: Planet is a global company that designs, builds, and operates the largest constellation of imaging satellites. They are seeking an AI/ML Software Engineer Intern to develop advanced machine-learning methods for geospatial analytics and computer vision.
Responsibilities:
- Develop novel AI/ML tools for image processing and geospatial analysis
- Collaborate with researchers and engineers to help translate prototype algorithms into production-ready software
- Design data processing workflows and storage approaches for managing large geospatial and embedding datasets
- Build tools to visualize, analyze, and communicate complex analytics and patterns
Required Qualifications:
- Passion for exploring state-of-the-art AI/ML applying ideas to real-world problems
- Programming skills in Python (or similar scientific/ML stack)
- Experience with numerical computing, data processing, and ML frameworks
- Currently pursuing a BS/MS/PhD in Computer Science, Machine Learning, Engineering, Applied Math, Physics, or related field
Preferred Qualifications:
- Ability to design and implement algorithms to solve real-world data problems
- Experience building data visualizations or analytics interfaces for geospatial analytics or remote sensing
- Curiosity and initiative to dive into unfamiliar technical domains and rapidly build understanding
- Willingness to collaborate openly, share ideas, and learn from teammates across disciplines
Required Skills: AI/ML algorithms, Python, Geospatial analytics
Important Skills: Numerical computing, Data processing
Nice-to-Have Skills: Curiosity
Benefits: Commuter Benefits, Paid time off for holidays and company-wide days off, Internet reimbursement, Access to LinkedIn Learning
Benefits
Commuter Benefits
Paid time off for holidays and company-wide days off
Internet reimbursement
Access to LinkedIn Learning