Deep Learning Engineer
Company Details
Earthcube is developing monitoring solutions based on an automated analysis of geospatial information. By combining state-of-the-art AI technics in both Computer Vision and Machine Learning, Earthcube enables its customers to access more precise information, thus ensuring faster and less costly interventions.
MAIN ACTIVITIES
- Developing and integrating in our AI framework the state-of-the-art methods of the deep learning literature or innovations from our AI R&D team (especially in the fields of segmentation, object detection, ensembling, and active/continuous learning).
- Ensuring the code quality of our AI framework, by applying good practices and by coaching others
- Contributing to the specifications of our AI framework to improve productivity
- Coming up with new ideas to push forward the performances of our AI framework.
- Understanding the needs and expectations for the detectors to improve in order to help to plan new developments.
- Work closely with the GIS team and business experts to understand those needs.
MUST-HAVES
- Education in the field of data science / deep learning / computer science (Master degree, or PHD)
- At least 3 years of experience in deep learning (also including internships, online courses, personal side projects, etc.)
- Very good understanding of deep learning techniques, especially CNNs for Segmentation and Object Detection
- Strong skills in programmation, in particular in python 3 (OO programming, tdd, or unit test are not unknown words for you)
- Agile development
- Rigorous, creative and meticulous mind
- Excellent organizational skills, autonomy, and reporting capabilities.
- Willingness to take on challenges, show resiliency and like to always learn new skills
NICE-TO-HAVES
- Strong knowledge in Computer Vision
- Proficiency with docker
- Experience working with remote sensing images (gdal, etc.)
- Experience working in a startup environment
- Skills in SQL, elasticsearch and JS
