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AI Inference Engineer for Embedded Platforms
2 months ago
About Invisible AI Inc.
At Invisible AI, we are pioneering advancements in computer vision technology. Our primary mission is to create a comprehensive platform that transforms manufacturing processes. By utilizing edge AI cameras, we aim to enhance the accuracy, reliability, and safety of manual assembly tasks, thereby revolutionizing people-driven manufacturing.
Our founders, who have extensive experience in the self-driving car industry, are committed to building and deploying robust AI and Machine Learning pipelines. We invite you to join our team and contribute to a company that is unlocking the vast potential of computer vision for real-world applications.
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 infrastructure across various hardware accelerators and deep learning inference platforms. Your work will be instrumental in shaping the future of our hardware solutions.
You will address the challenges associated with deploying machine learning models developed in diverse libraries on edge computing platforms, focusing on feasibility, computational efficiency, and runtime performance. Collaborating with a talented team of engineers, you will help launch innovative AI products that are ready for immediate use across multiple domains.
Key Responsibilities
- Implement Pytorch models on Nvidia Jetson platforms, applying 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.
- Investigate power consumption issues related to SSDs, USB cameras, AI boards, and CPU/GPU configurations.
- Examine the compatibility of different machine learning operations with various 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.
- Solid understanding of PCIe interfaces for NVMe drives, hardware accelerators, and WiFi modules.
- Comprehensive knowledge of machine learning concepts, including convolutions, encoders, decoders, optimizers, and loss functions, particularly in embedded environments.
- Familiarity with the complete Linux stack and debugging techniques.
- Experience with Nvidia Jetson platforms and a good grasp of their hardware components (tensor cores, DLA, video encoders, and decoders).
- Knowledge of various digital communication 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 adjustments based on market conditions and individual qualifications assessed during the interview process. Invisible AI is an equal opportunity employer and values diversity in the workplace.
