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Nvidia Senior System Software Engineer - Deep Learning 
India, Karnataka, Bengaluru 
959102692

Today
India, Bengaluru
time type
Full time
posted on
Posted 19 Days Ago
job requisition id

NVIDIA DRIVE® embedded supercomputing platforms process data from camera, radar, and lidar sensors to perceive the surrounding environment, localize the car to a map, then plan and execute a safe path forward. This AI platform supports , , and , plus other safety features—all in a compact, energy-efficient package. We need passionate, hard-working and creative people to help us tackle more of these challenging opportunities in Autonomous Driving and In-Car Infotainment.

What you’ll be doing:

  • Develop solutions around NVIDIA GPU and Deep learning accelerators to realize DNNs for ADAS Systems

  • Optimize DNNs for the GPU and other hardware accelerators like DLA using CUDA/TensorRT

  • Improve DNN architectures using ML algorithms on NVIDIA GPUs or DLAs

  • Conduct benchmarking and evaluation activities to continuously improve inference latency, accuracy and power consumption of DNNs

  • Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas to improve NVIDIA's automotive DNNs

  • Responsible for the technical relationship and assisting the automotive customer in building creative solutions based on NVIDIA technology

  • Collaborate with engineering teams in our US, APAC, India and Europe locations

What we need to see:

  • BS or MS degree in Computer Science, Computer Engineering or Electrical Engineering

  • Experience in developing or using deep learning frameworks (e.g. TensorFlow, Keras, PyTorch, Caffe, ONNX, etc.)

  • 12+ years of experience in optimising DNN Layers for GPU or other DSPs

  • Proficiency in C and C++ and Data Structures

  • Strong OS fundamentals and knowledge of CPU/GPU architecture

  • Familiar with state-of-the-artCNN/LSTM/Transformersarchitecture


Ways to stand out from the crowd:

  • Strong analytical and problem solving skills, with good attention to details

  • Background with NVIDIA software libraries such as CUDA and TensorRT

  • Experience in automotive development processes like ASPICE or ISO26262

  • Excellent communication and organization skills, good time management and task prioritisation

  • Open source project ownership or contribution, GitHub repositories, guiding and/or mentoring experience