EagleView
Bangalore
IT Service
Data Scientist I
Professional Experience: 1-3 years
Location: Bangalore
Required Skills:
- Prior experience developing deep learning models for computer vision applications. Hands on experience in areas like image classification, object detection and instance segmentation.
- Understanding of deep learning fundamentals including network architectures, training artefacts, overfitting and regularisation in neural networks, batch normalisation and so on.
- Proficiency in python.
- Proficiency in numpy and opencv.
- Proficient in at least one of the deep learning frameworks e.g. PyTorch, MxNet or Tensorflow.
- Familiarity contributing and maintaining code in github.
- Understanding of SQL and docker technology is a bonus.
Responsibilities:
- Contribute across different stages of deep learning model development including data collection, data cleaning, model development, validation and deployment.
- Develop deep learning models for a wide variety of tasks spanning object detection, segmentation, tracking, synthesise and so on.
- Continuously improve the quality and performance of existing deep learning models by applying latest research in the field.
- Contribute in developing models in areas like self-supervised and semi-supervised learning
Educational Background
B.Tech/M.Tech (Optional), B.Sc./M.Sc., Computer Science, Maths, Statistics or equivalent field
Data Scientist I
Professional Experience: 1-3 years
Location: Bangalore
Required Skills:
- Prior experience developing deep learning models for computer vision applications. Hands on experience in areas like image classification, object detection and instance segmentation.
- Understanding of deep learning fundamentals including network architectures, training artefacts, overfitting and regularisation in neural networks, batch normalisation and so on.
- Proficiency in python.
- Proficiency in numpy and opencv.
- Proficient in at least one of the deep learning frameworks e.g. PyTorch, MxNet or Tensorflow.
- Familiarity contributing and maintaining code in github.
- Understanding of SQL and docker technology is a bonus.
Responsibilities:
- Contribute across different stages of deep learning model development including data collection, data cleaning, model development, validation and deployment.
- Develop deep learning models for a wide variety of tasks spanning object detection, segmentation, tracking, synthesise and so on.
- Continuously improve the quality and performance of existing deep learning models by applying latest research in the field.
- Contribute in developing models in areas like self-supervised and semi-supervised learning
Educational Background
B.Tech/M.Tech (Optional), B.Sc./M.Sc., Computer Science, Maths, Statistics or equivalent field
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