Designation Offered:
Software Engineer
Job Responsibilities:
Work with deep learning experts to design and implement networks optimized for GPU-accelerated inference
Develop advanced inference engine techniques to enable real-time deployment of models
Deploy productized networks to run efficiently on our hardware
Develop tools for profiling, analyzing, and improving both training and inference performance
Experience:
A minimum of 2 years of relevant experience in a similar role
Qualification:
Bachelor of Engineering (BTECH / BE) or Masters (MTECH / MS / MCA ) in Computer Science / Information Science or
Ph.D in Computer Science
Skills Required:
Essential
Excellent in machine learning and deep learning concepts such as
Data understanding and analysis
Supervised/ Unsupervised/semi-supervised learning
CNN for classification
RNN for time series data analysis
Object detection and classification
Excellent C/C++ and Python programming and software design skills
Intimate understanding and hands on experience of using computer vision and machine learning libraries
such as Tensorflow, Caffe, Torch
Proven GPU programming (e.g., CUDA, OpenCL) track record
Desirable
Code contributions to an open-source deep learning community
Experience using GPU-accelerated libraries (e.g., cuDNN and cuBLAS)
Experience with code generation & optimization
Experience with network model compression and quantization
Exposure to TensorRT kinds of tool for DL implementation
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