AI Inference Engineer for Embedded Solutions

2 weeks ago


San Francisco, California, United States Invisible AI Inc. Full time

About Invisible AI Inc.
At Invisible AI, we are pioneering advancements in computer vision technology. Our primary objective is to create a comprehensive platform that enhances manufacturing processes through digitization. By deploying edge AI cameras, we aim to transform manual assembly tasks, ensuring accuracy, reliability, and safety in people-driven manufacturing. With a background in self-driving technology, our founders bring extensive experience in developing and implementing large-scale AI and Machine Learning systems. Join us in our mission to unlock the vast potential of computer vision for our clients.

Role Overview
As an Embedded Machine Learning Engineer, you will engage with state-of-the-art technologies to assess the performance of our machine learning framework across various hardware accelerators and deep learning inference platforms. Your contributions will be vital in shaping the next generation of our hardware solutions. You will address the complexities of deploying machine learning models from diverse libraries onto edge computing platforms, evaluating their feasibility, computational efficiency, and runtime performance. Collaborating with a talented team of engineers, you will help launch innovative AI products that operate seamlessly across different domains without extensive data collection periods.

Key Responsibilities

  • Implement Pytorch models on Nvidia Jetson platforms utilizing optimal TensorRT enhancements.
  • Connect off-the-shelf hardware accelerators with single-board computers such as Orange Pi and Raspberry Pi.
  • Work with various hardware accelerators (e.g., GPUs), troubleshoot issues, and refine C++ code for peak performance.
  • Analyze power consumption challenges involving SSDs, USB cameras, AI boards, and CPU/GPU.
  • Explore the compatibility of various machine learning operations across different computing platforms.

Qualifications

  • Graduate students specializing in Electrical Engineering with a focus on Machine Learning/Deep Learning for Computer Vision, or undergraduate students with relevant experience.
  • Strong proficiency in C++ and practical experience with embedded Linux systems.
  • Experience in developing and deploying machine learning algorithms.
  • Comprehensive understanding of PCIE interfaces for NVMEs, hardware accelerators, and WiFi modules.
  • Solid grasp of machine learning principles such as convolutions, encoders, decoders, optimizers, and loss functions, along with their implementation on embedded platforms.
  • Experience in working with and troubleshooting the complete Linux stack.
  • Familiarity with Nvidia Jetson platforms and their hardware components (tensor cores, DLA, video encoders & decoders, etc.).
  • Knowledge of various digital interfaces (I2C, SPI, USB, CAN, HDMI, DDR3/4).
  • Proficiency in scripting languages such as Python or Bash.
  • Experience with arm64 based platforms.

Compensation
The estimated hourly pay range for this position is between $45.00, subject to modification based on various factors, including market conditions and individual qualifications assessed during the interview process. Invisible AI is an equal opportunity employer, committed to diversity and inclusion in the workplace.



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