Job Description
The internship involves developing and optimizing machine learning models and vision-language models for analyzing geospatial satellite imagery, contributing to the creation of a Queryable Earth platform, and collaborating with research teams to advance remote sensing applications.
Key Responsibilities
- Optimize and fine-tune vision-language models (VLMs) for Earth observation data
- Create and optimize embeddings for large-scale satellite imagery datasets
- Design and execute machine learning workflows for geospatial analysis
- Contribute to the development of a natural language queryable Earth platform
- Collaborate with research scientists and engineers on remote sensing models
- Preprocess and label geospatial data for machine learning tasks
- Evaluate and improve algorithms for feature detection and classification in satellite imagery
Requirements
- Currently pursuing a graduate degree in Computer Science, Data Science, Remote Sensing, or a related field
- Proficiency in Python programming language
- Experience with deep learning frameworks such as PyTorch or TensorFlow
- Familiarity with computer vision techniques
- Familiarity with natural language processing techniques
- Knowledge of geospatial data formats and analysis tools such as GDAL, GeoPandas, Rasterio
- Experience with vector databases and similarity search algorithms is a plus
- Excellent problem-solving skills and ability to work in a dynamic research environment
- This position requires access to export-controlled information, and employment or hiring of a contractor is contingent upon the candidate's ability to access all applicable export-controlled information without additional export licensing being required by the Bureau of Industry and Security and/or the Directorate of Defense Trade Controls
Benefits & Perks
Compensation range: US hourly rate $35 - $60, final salary determined by experience, skills, and location
Work schedule: Full-time, 12-week summer internship, 5 days per week
Work environment perks: Commuter benefits, paid time off for holidays and company-wide days off, internet reimbursement, access to LinkedIn Learning
Ready to Apply?
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