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NVIDIA

Company: NVIDIA
Website: http://www.nvidia.com/page/home.html
Location: Santa Clara, California, US
Employees: 10,000+
Industry: Semiconductor - Specialized  in Deep Learning and AI
Founded:  1993
Introduction:  FROM GAMING TO AI COMPUTING

The GPU has proven to be unbelievably effective at solving some of the most complex problems in computer science. It started out as an engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films.

Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.

This is our life’s work — to amplify human imagination and intelligence.
   
Opening A: 2 persons
Field: Deep learning Solutions Architect - Autonomous Driving
Description:  Position 1: Deep learning Solutions Architect - Autonomous Driving (2 persons)
Projects/Tasks for 1-year program:
l New features development in TensorRT product.
l Working on building components of AI infra deployment.
l New features development in Driveworks.

Criteria:
l Background in Deep Neural networks and/or Computer vision
l Programming Skills – C/C++, Python
l Good to have GPU computing/CUDA background
l Problem solving skills
   
Opening B: 2 persons
Field: Deep Learning-Intelligent Video Analytics
Description:  Position 2: Deep Learning-Intelligent Video Analytics (2 persons)
Projects/Tasks for 1-year program:
• Development of face/people detection and recognition DL networks
• Design of networks for extraction of attributes from pedestrians and cars
• Tracking and Re-identification of peoples and cars
• Performance characterization of networks against KPI

Criteria:
• Knowledge of DL frameworks, and recent research in architectures
• Knowledge of computer vision
• Programming in Python and C/C++
   
Opening C: 6 persons
Field: General Deep Learning Solutions Architect- HealtheCare, DevTech
Description:  Position 3: General Deep Learning Solutions Architect- HealtheCare, DevTech  (4-6 persons)
Projects/Tasks for 1-year program:
• To integrate NVIDIA technology into HPC and Cloud architectures to support Artificial Intelligence research and applications.
• Develop GPU-accelerated applications, design examples and solutions using NVIDIA technologies.
• Document all aspects of research and benchmarking results to contribute to the knowledge base of NVIDIA
• Develop effective curriculum and training content for data scientists and software developers
• Product testing and qualification at customer premises (if required) including, reviewing, identifying, reproduction of customer bugs.

 Criteria:
• Experience working with modern Deep Learning software architecture and frameworks including Caffe, Theono, Tensorflow, Convnet,  cuDNN, Torch or other Deep Learning Frameworks
• C programming / Parallel programming experience
• Exposure to GPU technology
• CUDA optimization,  CUDA  Programming experience
• Specialty skills in large scale computing and cluster computing, machine learning, convolution neural networks