Embedded Machine Learning Engineer - Co-Op/Intern

Invisible AI

Invisible AI

Software Engineering
San Francisco, CA, USA
Posted on Thursday, July 11, 2024
At Invisible AI, we are building the future of computer vision. Today, our core focus is on developing an end-to-end platform that can digitize manufacturing operations. We deploy edge AI cameras to digitize all steps of manual assembly work which helps people-driven manufacturing be accurate, reliable, and safe. Coming from the world of self-driving cars, the founders of Invisible AI have years of experience in building and deploying large-scale AI & Machine Learning pipelines. Join us and help build a company that will deliver the endless possibilities of computer vision to real-world customers!
As a Machine Learning Inference Engineer Intern/Co-Op, you will be working with cutting-edge technologies to validate the performance of our machine learning stack on different off-the-shelf hardware accelerators and deep learning inference platforms. This will contribute to the next generation of our hardware. You will be tackling the challenges of deploying machine learning models built in different libraries on edge compute platforms analyzing feasibility, and computational and runtime performance of the models. You will be working with a world-class team of engineers to deploy a new wave of AI products that work out-of-the-box across domains without weeks or months of data collection.
We are looking for Graduate students with backgrounds in Electrical Engineering and focus on Machine Learning/Deep Learning for Computer Vision. Undergraduate students with relevant experience are encouraged to apply.

Recent projects for this role include:

  • Deploy Pytorch models on Nvidia Jetson platforms using best TensorRT optimizations.
  • Interfacing off the shelf hardware accelerators with single board computers like Orange Pi and Raspberry Pi.
  • Interfacing with various hardware accelerators (e.g. GPUs), debugging issues, and optimizing C++ code to maximize performance.
  • Debugging issues with power draw from an SSD, USB camera, AI board, and CPU/GPU.
  • Investigating the support for various machine learning operations on different compute platforms.

Requirements:

  • Graduate student with a background in Electrical Engineering focused on Machine Learning/Deep Learning for Computer Vision, or, Undergraduate students with relevant experience.
  • High Proficiency in C++ with hands-on experience in embedded Linux.
  • Experience with writing and deploying machine learning algorithms.
  • Solid understanding of PCIE interfaces for NVMEs, HW accelerators and WiFi cards.
  • Solid knowledge of ML concepts like convolutions, encoders, decoders, optimizers, loss functions, and their implementation on an embedded platform.
  • Experience working with and debugging the full Linux stack system.
  • Experience/familiarity with Nvidia Jetson platforms and understanding of their HW components (tensor cores, DLA, video encoders & decoders etc.)
  • Experience with various digital interfaces (I2C, SPI, USB, CAN, HDMI, DDR3/4)
  • Familiarity with any scripting language like Python or Bash.
  • Experience working with arm64 based platforms.
The estimated hourly pay guideline range for this role is between $30.00 - $45.00 and may be modified. This will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. Invisible is an equal opportunity employer. We do not discriminate based on age, ethnicity, gender, nationality, religious belief, or sexual orientation.