Cynet Systems

Proficient with deep learning algorithms especially towards developing computer vision applications.. Strong experience in using both basic and advanced image processing algorithms for feature engineering.. Ability to read and implement related academic literature and experience in applying state-of-the-art deep learning models to computer vision (e.g. segmentation, detection) or other areas as (speech, NLP, GANs).. Profound and proven knowledge in tools and programming languages like TensorFlow, KERAS, Tytorch, Matlab, Python; knowledge in embedded C/C. Strong experience with data science tools including Python scripting, CUDA, numpy, scipy, matplotlib, scikit-learn, bash scripting and Linux environment.

data scientist

Job Description: Pay Range $60hr - $65hr Excellent knowledge in LLM specifically expertise in open AI skills including GPT 3.5, GPT 4 Experience of developing solutions using AI & Client technology.
Proficient with deep learning algorithms especially towards developing computer vision applications.
Excellent knowledge of FCN, CNN, DNN and sequential neural network architectures.
Strong experience in using both basic and advanced image processing algorithms for feature engineering.
Ability to read and implement related academic literature and experience in applying state-of-the-art deep learning models to computer vision (e.g. segmentation, detection) or other areas as (speech, NLP, GANs).
Knowledge on sensors and vision systems, sensor integration and fusion.
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 embedded platforms, including different GPU architectures.
Profound and proven knowledge in tools and programming languages like TensorFlow, KERAS, Tytorch, Matlab, 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.
Proficiency with edge computing principles and architecture on commonly used popular platforms.
Experience in different model optimization techniques apart from hyperparameter tuning to reduce memory usage without hindering the performance for deploying on edge devices. BARD, Cohere, PaLM, and Claude v1 etc will be an added Advantage. #J-18808-Ljbffr

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