Research & Development

Data Scientist (Deep-learning Development - 2D Image)

Collaborate with the research and development team to design and develop deep learning models and algorithms for 2D image semantic segmentation and object recognition
Implement and fine-tune state-of-the-art deep learning architectures such as SAM, Mask R-CNN or other models to achieve accurate and efficient segmentation results.
Preprocess and augment image datasets to improve model performance and generalization.
Train and validate deep learning models using large-scale annotated datasets and existing datasets from the company.
Evaluate and analyze model performance by using appropriate metrics and statistical techniques.
Stay up-to-date with the latest advancements in deep learning and computer vision, and propose innovative ideas to improve our segmentation algorithms.
Collaborate with cross-functional teams, including data scientists, GIS analyst and programmer, to integrate the developed models into our software solutions.

Currently pursuing a bachelor's or master's degree in computer science or a related field with a focus on machine learning, computer vision, or deep learning.
Strong understanding of deep learning concepts, architectures, and frameworks such as TensorFlow, PyTorch, or Keras.
Familiarity with image processing and computer vision algorithms.
Proficiency in programming languages such as Python and C++.
Knowledge of semantic segmentation techniques and experience with related frameworks like Mask R-CNN, SAM, or DeepLab V3+ is a plus.
Solid understanding of machine learning fundamentals, including data preprocessing, model training, and evaluation.
Experience with deep learning model deployment and optimization techniques is desirable.
Strong problem-solving skills and the ability to think critically and creatively.
Excellent communication and teamwork skills to collaborate effectively with cross-functional teams.
Attention to detail and a commitment to producing high-quality results.

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