Data Science Engineer
Pubblicato il 03-10-2026 - Verizon in San Miniato
Overview
Join Verizon's AI team to design, train, and optimize ML and CV models powering edge devices and cloud backends. You will collaborate with cross-functional teams to deliver reliable, high-performance AI solutions that improve device health, usage insight, and user safety. This role blends research, practical deployment, and production-ready software to impact a global product ecosystem. You'll work in Florence with a hybrid schedule and have opportunities to shape innovative AI applications at scale.
Retribuzione / Benefits
competitive pay and performance-based incentives
health and wellbeing resources
Employee Assistance Program
paid time off
flexible working arrangements
training and development funding
Responsabilità
Design, train, and evaluate ML, computer vision, and deep learning models for edge devices and cloud backends
Curate large-scale labeled, pseudolabeled, or synthetic datasets with quality and privacy compliance
Benchmark and optimize models for memory, latency, and power constraints
Write high-quality, production-ready code with TDD, CI/CD, and solid software design
Collaborate with embedded software, firmware, product, and hardware teams to integrate models into devices and pipelines
Support model deployment and establish monitoring workflows for health and drift in production
Conduct research, build POCs on emerging AI/CV technologies, and contribute to innovation goals
Requisiti fondamentali
Master in Computer Science, Software Engineering or equivalent
Experience with Python and ML/DL libraries (PyTorch, TensorFlow, NumPy, Pandas)
Hands-on CV/ML model development and evaluation on real-world datasets
Familiarity with Git, unit testing, and modular code design
Experience using AI coding assistants
Knowledge of Agile development workflows
excellent communication
cross-functional collaboration
problem solving and adaptability
edge/embedded model optimization (ONNX, TensorRT, TFLite, quantization/pruning)
production integration with C/C++ or Rust
multimodal data processing (e.g., CV with time-series data like IMU, GPS, telematics)