INNOITALY

INNOITALY S.R.L.

ROVERETO

Innoitaly S.r.l. is a start-up founded in October 2023 that focuses on designing, developing, planning, and producing energetically autonomous and batteryless sensory devices within a circular economy, including data processing, both embedded on the sensor with AI and on the cloud and blockchain.
Specifically, the company’s core business is the research, development, design, and production of energetically autonomous and recyclable (second life) sensor networks (also printed).
Innoitaly’s goal is to process data derived from sensors to reduce consumption in buildings, improve indoor (greenhouse, hydroponic, vertical farm) and outdoor cultivation in agritech, create wearable and biodegradable sensors in the medical field, and optimize the management of urban waste, including logistics.
Innoitaly aims to create a nearly fully recyclable and batteryless hardware platform within a circular economy and a cloud platform, including blockchain, for data management and certification, even for scientific use.

INNOITALY

INNOITALY S.R.L.

ROVERETO

Innoitaly S.r.l. is a start-up founded in October 2023 that focuses on designing, developing, planning, and producing energetically autonomous and batteryless sensory devices within a circular economy, including data processing, both embedded on the sensor with AI and on the cloud and blockchain.
Specifically, the company’s core business is the research, development, design, and production of energetically autonomous and recyclable (second life) sensor networks (also printed).
Innoitaly’s goal is to process data derived from sensors to reduce consumption in buildings, improve indoor (greenhouse, hydroponic, vertical farm) and outdoor cultivation in agritech, create wearable and biodegradable sensors in the medical field, and optimize the management of urban waste, including logistics.
Innoitaly aims to create a nearly fully recyclable and batteryless hardware platform within a circular economy and a cloud platform, including blockchain, for data management and certification, even for scientific use.

Job opportunities

Application engineer profile on (tiny) machine learning

Number of open position: 1
Place of work: Rovereto
Published on: 27/09/2024
Deadline for applications: 18/11/2024
Full-time job

Job description:

For the new office located in Rovereto (Trento), Innoitaly is looking for an Application engineer profile on machine learning on embedded systems with the goal to design and implement a novel framework to support the development of green and even fully sustainable Tiny Machine Learning applications distributed in an edge-to-cloud continuum. The objective is to design and develop techniques for energy-efficient Tiny Machine Learning on low-cost and low-power microcontrollers characterized by memory-constraints and powered with an unregular supply coming from energy harvesters. Tasks include:

  • efficient data collection, AI model generation (neural networks), compression, and code generation for memory-constrained IoT devices
  • intermittent execution and acceleration of the trained ML model on microcontrollers
  • the activity will be intersecting with the following topics: Energy Efficient and Low-Power Computing; Machine Learning on Microcontrollers (Tiny Machine Learning); Embedded Systems and Software Support; Architectural and Hardware Support

Job Requirements

  • Master degree (or equivalent) in computer science and engineering, electronics, electrical engineering or telecomunication
  • the ideal candidate is a team player who works well in collaborative situations and challenging environments. He/she has a strong problem-solving approach, results orientation, a sense of urgency, and proactivity skills. Previous experience will be considered an added value.
  • requirements: Machine Learning Algorithms and Deep Neural Networks; Compilers, Efficient Code Generation; Good programming skills (Python/C/C++/Assembly Language); Programming Microcontrollers, and Interfacing Sensors; (Optionally) Basic Electronics, PCBs, Circuits

Details

  • full time
  • possibility of two days of remote work
  • permanent contract

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