Embedded Machine Learning Engineer Co-Op/Intern, Invisible AI
$30.00 - $45.00 per hour
Optimizing manufacturing with computer vision AI
Job no longer available
Optimizing manufacturing with computer vision AI
21-100 employees
Job no longer available
$30.00 - $45.00 per hour
21-100 employees
Company mission
To maximize the output of every business by providing visibility and insight into the physical world.
Role
Who you are
- 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
- 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
What the job involves
- 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
- 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
Our take
An estimated two-thirds of manufacturers are using AI in their day-to-day operations, fueling the race to modernize manufacturing plants and warehouse floors. Invisible AI, a leader in state-of-the-art AI solutions for manufacturing, has developed a computer vision platform that tracks workers’ body movements throughout the assembly process.
From safety audits to continuous improvement cycles, manufacturing data is traditionally collected by manually using stopwatches and clipboards. Currently utilized in a number of facilities (including Toyota, Fuji, and Siemens), and with several new deployments on schedule, Invisible AI optimizes assembly operations, providing operators with real-time feedback to ensure processes are done correctly and safely.
Backed by leading investment companies including Van Tuyle Companies, 8VC and Sierra Ventures, the company’s scalable, next-generation computer vision system revolutionizes the data collecting process of manual manufacturing operations. Invisible AI is leading the way to the fourth industrial revolution, empowering manufacturing industries worldwide to accelerate the adoption of industry 4.0.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Sep 2022
$15m
SERIES A
Jul 2021
$2.5m
EARLY VC
Total funding: $21.1m
Company benefits
- Health/Vision/Dental Insurance (100% coverage for employees, 50% for dependents)
- Flexible Vacation Schedule
- Equity Packages
Company HQ
University South, Palo Alto, CA
Leadership
Eric Danziger
(Co-Founder & CEO)Previously worked at Luminar Technologies as a Senior Engineer, Director of Engineering, and Advisory Director of Engineering. Former Senior Engineer at Cogniac and was a Laboratory Technician at the University of Virginia.
Prateek Sachdeva
(Co-Founder & CPO)Founded and was CEO of Boldr. Co-founded and was Lead Engineer at ScheduleMe. Worked at Luminar Technologies as a Software Engineer and Technical Product Manager. They have also invested in numerous companies.
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