R&D Deep Learning Software Senior Engineer (10846)

Datalogic; Monte San Pietro; In loco; EUR 50.000 - 75.000; Tempo pieno

Descrizione del lavoro

A leading company in the AI sector is seeking a Senior Embedded Deep Learning Engineer to enhance its product portfolio in barcode and 2D code localization. The candidate will design and deploy innovative AI/ML models on edge devices, contributing to the future of AI solutions with a hands-on approach. Applicants should have extensive experience in deep learning technologies and strong programming skills, alongside a collaborative mindset.

Competenze

• At least 5 years of experience in Deep Learning/Computer Vision research.
• Good knowledge of ML/Deep Learning models for regression and classification tasks.
• Experience developing embedded or edge device products through full lifecycle.

Mansioni

• Design and develop AI-based algorithms for data localization and decoding.
• Research and develop machine learning models for automatic data analysis.
• Integrate ML components into existing products and optimize processing pipelines.

Conoscenze

Deep Learning

Computer Vision

Machine Learning

C++

Python

Formazione

PhD preferred or MS in Computer Science, Math, Physics, Electronic Engineering, Artificial Intelligence

Strumenti

TensorFlow

PyTorch

Descrizione del lavoro

Job Description
We are looking for a highly motivated Senior Embedded Deep Learning Engineer to join the Computer Vision & Machine Learning team that is in charge of expanding the AI product portfolio of Datalogic, focused primarily on the utilization of Artificial Intelligence to improve and speed up the localization and decoding phase of barcode and 2D codes. Headquarter Lippo di Calderara (BO).
The role is responsible for designing and developing both AI-based and computer vision algorithms to extract information automatically from a continuous stream of data. As a Senior Engineer, you will be hands-on and responsible for deployment of the deep learning models directly at the edge. In this role, you will contribute extensively to Datalogic edge devices, creating AI/ML models as well as classic algorithms, taking a science first approach, integrating them into the underlying architecture, code maintenance, QA efforts and everything alse involved in the end-to-end product development and release cycles. The candidate will work closely with other engineers and scientists creating the foundation of the future Datalogic AI solutions.
Key Responsibilities:
* Research and develop state-of-the-art Machine Learning/Deep Learning models for automatic data analysis;
* Design and implement DNNs and other ML techniques to detect and classify 2D codes acquired from a camera;
* Train, optimize, quantize, deploy and monitor performances of DNNs on edge devices;
* Analyze performance of models, provide guidance for targeted data collection to enhance training dataset;
* Integrate ML components into existing products by optimizing the entire processing pipeline;
* Work cross functional to help define product requirements aligning the technical agenda with the company's business objectives.
Requirements:
* Education: PhD preferred or MS in Computer Science, Math, Physics, Electronic Engineering, Artificial Intelligence
* Languages: Italian, English proficient
* Experience: At least 5 years of experience in research activity on Deep Learning/Computer Vision. Good knowledge of ML/Deep Learning models used both regression and classification tasks.
Other Information and Specific Skills:
> Technical Skills:
* MS in Computer Science, Math, Physics, Electronic Engineering, with a focus in Deep Learning, Computer Vision, Artificial Intelligence or related fields.
* At least five years' experience developing embedded or edge device through full product lifecycle.
* At least five years' experience developing machine learning/deep learning/computer vision algorithms running on edge devices.
* Consolidated knowledge of ML framework such as TensorFlow or PyTorch.
* Good programming skills both in C++ and Python.
> Soft Skills:
* multidisciplinary team working;
* mentoring junior colleagues;
* willingness to work with international teams;
* active participation to the project, and commitment to quality and time.
* Practical mind set and co-attitude
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