Rubicon

www.rubicontechnology.ai

1 Job

5 Employees

About the Company

Rubicon uses lower-frequency radar data to look beneath the surface of the Earth and uncover what other sensors can’t.
We provide insights and intelligence to various industries, incl. Environment, Earth Sciences, and Security.

Listed Jobs

Company Name: Rubicon
Job Title: Computer Vision Engineer
Job Description: **Job Title** Computer Vision Engineer **Role Summary** Develop and deploy deep learning models for Earth observation using multispectral, hyperspectral, LiDAR, and SAR data. Work closely with research teams and software engineers to transform algorithms into commercial solutions and provide technical support to customers. **Expactations** * Deliver scalable, high‑performance models on large satellite datasets. * Own the end‑to‑end model lifecycle, from data preparation to deployment. * Iterate quickly under incomplete specifications and collaborate transparently across disciplines. * Demonstrate a practical, solution‑oriented mindset rather than academic perfection. **Key Responsibilities** * Gather, clean, and structure raw satellite imagery; assess data quality. * Design, train, and refine CNN/Deep Learning algorithms on terabytes of data. * Validate models with researchers, fine‑tune hyperparameters, and document results. * Integrate models into end‑to‑end commercial products and support them in production. * Contribute to codebases, MLOps pipelines, and overall software development activities. **Required Skills** * Proficiency in Python with libraries: Scikit‑learn, TensorFlow‑Keras, PyTorch. * Expertise in deep learning for Earth‑remote sensing, including CNNs and data‑augmentation techniques. * Strong data‑engineering skills: handling GeoTIFF, HDF5, SAR, LiDAR, and multispectral formats. * Basic MLOps: model versioning, CI/CD, containerization, and cloud deployment. * Autonomous problem‑solving, rapid iteration, and cross‑functional collaboration. * Experience with SAR data is a plus. **Required Education & Certifications** * PhD or Master’s in Engineering, Computer Science, Remote Sensing, or a related field with coursework in machine learning and Earth observation. ---