Algorithm Engineer

Overview

As part of the Decoding Software team, you will contribute to the design and development of the software library that reads barcodes and OCR text on edge devices. You will advance multi-threaded signal and image processing components across diverse edge platforms, from CPUs to accelerators, while integrating ML-driven decoding methods. You will help improve usability and performance to maintain leadership in decoding solutions. This role offers hands-on work on cutting-edge computer-vision and ML techniques within a scalable, cross-platform architecture.

Responsabilità

• Design and develop multi-threaded signal/image processing libraries for edge platforms with varying CPU architectures and OS
• Develop new software components following SQA best practices
• Research and integrate next-generation decoding algorithms based on ML and traditional CV
• Integrate ML-based algorithms into the existing Decoding-Library architecture (1D/2D codes)
• Improve ease-of-use and performance of the Decoding-Library to support product leadership
• Maintain released versions via debugging, analysis, and defect fixing
• Migrate to an Agile delivery approach enabling autonomous builds/releases and CI/CD integration
• Collaborate across cross-functional teams to optimize decoding pipelines
• Contribute to ongoing platform optimization for different hardware accelerators (CPU, GPU, FPGA, SIMD)

Requisiti fondamentali

• Master’s Degree in Computer or Electronic Engineering or Mathematics or Physics
• Italian and English (intermediate or better)
• Strong knowledge of C/C++
• Hands-on debugging, profiling, and code analysis
• Experience in analysis, understanding, and optimization/refactoring of existing code
• Experience in design of signal/image-processing algorithms
• Experience in image-processing acceleration (OpenMP, FPGAs, GPUs, SIMD, NN inference accelerators) preferred
• Knowledge of DevOps tools (Git, Docker, Jenkins) and CI/CD principles preferred
• C/C++ programming
• debugging and profiling
• signal/image-processing algorithm design
• image-processing acceleration (OpenMP, FPGAs, GPUs, SIMD)
• Neural Network Inference accelerators
• DevOps tools (Git, Docker, Jenkins)

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