Job Description
At Invisible AI, we are building the future of computer vision. Our core focus is on developing an end-to-end platform that digitizes manufacturing operations. We deploy edge AI cameras to digitize all steps of manual assembly work, enhancing accuracy, reliability, and safety in people-driven manufacturing. Our founders bring years of experience from the self-driving car industry, specializing in large-scale AI & Machine Learning pipelines. Join us to help deliver the endless possibilities of computer vision to real-world customers!
Role Overview
As an Embedded Machine Learning Engineer Intern/Co-Op, you will work with cutting-edge technologies to validate the performance of our machine learning stack on various hardware accelerators and deep learning inference platforms. Your contributions will be crucial to the next generation of our hardware. You will tackle challenges in deploying machine learning models built in different libraries on edge compute platforms, analyzing feasibility, and computational and runtime performance of the models. Collaborate with a world-class team of engineers to deploy a new wave of AI products that work out-of-the-box across domains without extensive data collection.
Key Responsibilities
- Deploy Pytorch models on Nvidia Jetson platforms using TensorRT optimizations.
- Interface off-the-shelf hardware accelerators with single-board computers like Orange Pi and Raspberry Pi.
- Debug and optimize C++ code to maximize performance on various hardware accelerators (e.g., GPUs).
- Investigate support for various machine learning operations on different compute platforms.
Requirements
- Graduate student in Electrical Engineering with a focus 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 in writing and deploying machine learning algorithms.
- Solid understanding of PCIE interfaces for NVMEs, HW accelerators, and WiFi cards.
- Knowledge of ML concepts like convolutions, encoders, decoders, optimizers, and loss functions, and their implementation on an embedded platform.
- Experience with the full Linux stack system and debugging.
- Familiarity with Nvidia Jetson platforms and understanding of their HW components (tensor cores, DLA, video encoders & decoders, etc.).
- Experience with digital interfaces (I2C, SPI, USB, CAN, HDMI, DDR3/4).
- Familiarity with scripting languages like Python or Bash.
- Experience with arm64 based platforms.
Compensation
- The estimated hourly pay range for this role is between $30.00 - $45.00, subject to modification based on market and individual qualifications assessed during the interview process.
Invisible AI is an equal opportunity employer. We do not discriminate based on age, ethnicity, gender, nationality, religious belief, or sexual orientation.
Benefits Extracted with AI
- Equal opportunity employer
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