Senior C++ Engineer, Deep Learning, GPU Optimization

September 13

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Logo of Torc Robotics

Torc Robotics

autonomous vehicles β€’ automotive autonomy β€’ self-driving cars β€’ autonomous mobility β€’ autonomous trucks

501 - 1000

Description

β€’ Optimize machine learning inference models for NVIDIA Orin execution β€’ Leverage data parallelism and CUDA programming β€’ Implement tensorrt plugins β€’ Stay abreast of the latest advancements in PyTorch, maximizing their potential for target hardware execution β€’ Collaborate with machine learning engineers to develop innovative and performant deep learning solutions β€’ Analyze and optimize deep learning inference using profiling and optimization tools, identifying and eliminating performance bottlenecks β€’ Contribute to the development of internal tools and libraries to further enhance deep learning performance on the target hardware β€’ Document your work clearly and concisely, sharing knowledge effectively with team members

Requirements

β€’ Bachelor's degree in computer science, data science, artificial intelligence or related field with 6+ years of professional experience or a master's degree with 3+ years of experience β€’ Mastery of Modern C++ (14 or more recent) and Python, with the ability to write efficient and maintainable code for both performance and flexibility β€’ Familiarity with object-oriented software design patterns, and their implementation in C++ β€’ In-depth knowledge of CUDA programming and experience with optimizing deep learning kernels β€’ Excellent understanding of parallel computing (GPGPU) and high-performance (HPC) concepts β€’ Excel at working in a highly collaborative environment: β€’ Familiarity with AGILE development practices β€’ Comfortable using collaborative development tools such as Git and Jira β€’ Ability to adhere to company coding standards β€’ Proven dedication to writing production-quality code that is robust, efficient, portable, maintainable, and bug-free β€’ Phd with 1+ years of experience β€’ Experience working on safety critical systems β€’ Experience with other relevant NVIDIA libraries and frameworks, such as CUBLAS, CuDNN, and NPP β€’ Deep Learning frameworks such as TensorFlow, PyTorch, or Caffe

Benefits

β€’ A competitive compensation package that includes a bonus component and stock options β€’ 100% paid medical, dental, and vision premiums for full-time employees β€’ 401K plan with a 6% employer match β€’ Flexibility in schedule and generous paid vacation (available immediately after start date) β€’ Company-wide holiday office closures β€’ AD+D and Life Insurance

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