Key Responsibilities
- Develop models for precision agriculture, including field recognition and attribute identification from satellite images using advanced machine learning algorithms.
Must-Have Qualifications
- 5+ years of experience in a relevant field.
- Proficiency in Python (C++ is a plus).
- Expertise in modern ML/DL/CV techniques (Semantic Segmentation, Instance Segmentation, Object Detection, Time Series Analysis).
- Experience with OpenCV, scikit-learn, scikit-image.
- Proficiency in PyTorch.
- Proficiency in classical machine learning and computer vision algorithms.
- Ability and willingness to read and understand contemporary ML/DL research papers.
- Strong mathematical foundation: statistics, probability theory, algorithms.
- Strong problem-solving skills and the ability to propose solutions independently.
- Ability to work effectively in a strong team environment.
- Quick learner.
- At least an intermediate level of English language proficiency.
Additional Advantages
- Experience with GIS (GDAL).
- Familiarity with classic backend technologies: FastAPI, Django, Celery.
- Experience with PostgreSQL, PostGIS.
- Proficiency in Linux/BASH/Docker.
- Experience with Docker/Kubernetes.
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