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Salary
≈ $22k – $49k per year (Estimated)
Location
Hybrid (Florence, Italy)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 5, 2026. First seen by Alion on Oct 1, 2026.

Overview
Company
Impact
Profile match
Verizon Communications is a telecommunications company headquartered in New York City, providing wireless phone and data service, Fios fiber internet and TV, 5G home and business broadband, and network, security and IoT solutions for enterprises and government. Formed in 2000 from the merger of Bell Atlantic and GTE and listed on the New York Stock Exchange, it runs major operations in Basking Ridge, Irving, Ashburn, Alpharetta and Cary, plus technology centers in Hyderabad and Chennai. It hires retail sales associates, small business account managers, SLED and enterprise sales executives, network and AI engineers, data scientists and legal and tax counsel.
Backed by Matrix

When you join Verizon

You want more out of a career. A place to share your ideas freely - even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love - driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together - lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife.

What you’ll be doing...

Our customers rely on the physical connected devices we build. Delivering a top-notch experience requires analyzing high-volume telemetry and video/sensor streams to monitor device health, understand usage patterns, and enhance driver and user safety.

That’s where you come in. Joining our AI team, you will design, train, and optimize the models that power our product ecosystem, ranging from ultra-lightweight, low-latency models running directly on edge hardware to large multimodal architectures in the backend.

You will be based in our Florence office with a flexible hybrid schedule, working as part of a global, cross-functional team.

Responsibilities:

  • Designing, training, and evaluating Machine Learning, Computer Vision, and Deep Learning models for both edge devices and cloud backends.
  • Collecting, cleaning, annotating, and verifying large-scale datasets (labeled, pseudolabeled, or synthetic) while ensuring data quality and privacy compliance.
  • Benchmarking and optimizing models to run efficiently within hardware resource constraints such as memory footprint, latency, and power consumption.
  • Writing high-quality, maintainable, and production-ready code following TDD, CI/CD, and robust software design practices.
  • Partnering closely with embedded software, firmware, product, and hardware engineering teams to integrate models into physical devices and cloud pipelines.
  • Supporting model deployment and establishing monitoring workflows to track model health and performance drift in production.
  • Carrying out research, building POCs on emerging AI/CV technologies, and contributing to company innovation goals.

What we’re looking for...

You’ll need to have...

  • Master’s degree in Computer Science, Software Engineering or equivalent relevant work experience.
  • Experience working withPython and standard ML/DL libraries (pytorch, tensorflow, numpy, pandas).
  • Hands-on experience developing, training, and evaluating Computer Vision or Machine Learning models on real-world datasets.
  • Familiarity with software engineering best practices (Git, unit testing, modular code design).
  • Experience using AI coding assistants.

Even better if you have…

  • Experience with model optimization for edge/embedded deployment (e.g., ONNX, TensorRT, TFLite, model quantization/pruning).
  • Experience working with C/C++ or Rust for production integration.
  • Background in multimodal data processing (e.g., combining computer vision with time-series sensor data like IMU, GPS, or telematics).
  • Exposure to MLOps tooling (MLflow, Docker, CI/CD pipelines) or cloud platforms (AWS/GCP/Azure).
  • Excellent communication skills and ability to work in a cross-functional team
  • Knowledge of Agile development workflows.

Why Verizon?

Verizon is committed to maintaining a Total Rewards package which is competitive, valued by our employees, and differentiates us as an Employer of Choice.

  • We are a ‘pay for performance’ company and your contribution is rewarded through competitive salaries and performance-based incentives. We create an opportunity for us all to share in the success of Verizon and the value we help to create through this broad-based discretionary equity award program.
  • Your benefits are market competitive and delivered by some of the best providers.
  • You are provided with a full spectrum of health and wellbeing resources, including a first in-class Employee Assistance Program, to empower you to make positive health decisions.
  • We offer generous paid time off benefits to help you manage your work life balance and opportunities for flexible working arrangements*.
  • Verizon provides training and development for all levels, to help you enhance your skills and develop your career, from funding towards education assistance, award-winning training, online development tools and access to industry research.
  • You will be able to take part in volunteering opportunities as part of our environmental, community and sustainability commitment.

Benefit packages are tailored to the specific country where a position is based.

If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.

Where you’ll be working

In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager.

Scheduled Weekly Hours

40

Equal Employment Opportunity

Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.

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