Model Development
Location : Bangalore
Position : 1
Required Experience : 5+ Years
Educational Qualification : B.Tech/ B.E.
Job Summary :
- Proven expertise in developing and training state-of-the-art algorithms to perform visual recognition tasks, such as segmentation, detection, and classification at scale.
- Proven expertise in Integrating deep neural networks and the associated preprocessing and postprocessing code to run efficiently on different GPU architectures.
- Profound and proven knowledge in tools and programming languages like TensorFlow, KERAS, Pytorch, Python; knowledge in embedded C/C++ is an advantage.
- Strong experience with data science tools including Python scripting, CUDA, numpy, scipy, matplotlib, scikit-learn, bash scripting and Linux environment.
- Knowledge of GStreamer, Deepstream and TensorRT.
- Knowledge of machine vision systems and camera.
- Good to have experience in using both basic and advanced image processing algorithms for feature engineering.
- Good to have knowledge of streaming protocols like RTSP,HLS.
- Good to have knowledge of Containerized deployments.
- Proficiency with edge computing principles and architecture on commonly used popular platforms.
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Job Summary :
- Proven expertise in developing and
training state-of-the-art algorithms to
perform visual recognition tasks, such as
segmentation, detection, and
classification at scale. - Proven expertise in Integrating deep
neural networks and the associated preprocessing and postprocessing code
to run efficiently on different GPU architectures. - Profound and proven knowledge in tools
and programming languages like
TensorFlow, KERAS, Pytorch, Python; knowledge in embedded C/C++ is an advantage. - Strong experience with data science
tools including Python scripting, CUDA, numpy, scipy, matplotlib, scikit-learn,
bash scripting and Linux environment. - Knowledge of GStreamer, Deepstream
and TensorRT. - Knowledge of machine vision systems
and camera. - Good to have experience in using both
basic and advanced image processing
algorithms for feature engineering. - Good to have knowledge of streaming protocols like RTSP,HLS.
- Good to have knowledge of
Containerized deployments. - Proficiency with edge computing
principles and architecture on
commonly used popular platforms.