AI Engineer (Google Cloud) Job in Milan | Salary & Hiring Insights

📍 Location: eu

🏷 Type: Not specified

Job Intelligence

📍 More in this location:
Browse AI jobs in eu

🏷 Similar roles:

🌐 Explore all jobs:
View all AI job listings

Job Overview

This Mid-Level AI Engineer role focuses on building scalable Machine Learning systems within a cloud-native (Google Cloud) environment. You will join Datwave (part of BIP), working on production-grade AI solutions across industries. The ideal candidate has 2–5 years experience, strong coding ability, and hands-on exposure to MLOps, data pipelines, and ML deployment. This is a hybrid consulting-engineering role requiring both technical execution and proactive innovation in AI-driven business solutions.

🌍 Work Eligibility & Location

This role is primarily Italy-based with hybrid flexibility, requiring onsite presence in Milan. The absence of clear visa sponsorship signals makes it less accessible to international candidates without EU work authorization. Strong Italian language proficiency is a strict requirement, reinforcing its local hiring focus despite global tech stack exposure.

💰 Salary Intelligence

For Milan-based AI roles, this estimated range is competitive within consulting firms but slightly below top-tier product companies. The value proposition comes from rapid skill development, enterprise exposure, and cloud specialization rather than pure compensation. Candidates should evaluate this role as a career accelerator rather than a salary-maximization opportunity.

📊 Role Breakdown

This role blends Machine Learning engineering (40%), cloud architecture and deployment (30%), and MLOps and collaboration (30%). You will design and implement scalable ML solutions using Google Cloud Platform (GCP), ensuring production readiness in terms of performance, security, and governance. A major portion of your work involves industrializing ML models, transforming prototypes into reliable systems through CI/CD pipelines, monitoring, and observability frameworks.

You will actively collaborate with Data Scientists, Cloud Architects, and Data Engineers, contributing to end-to-end ML lifecycle development. Beyond execution, the role requires innovation and research contributions, including scouting new AI solutions, proposing concepts, and supporting business development initiatives. This positions you not just as an engineer but as a strategic contributor to AI-driven transformation.

Exposure to Big Data ecosystems (Spark, Kafka) and Deep Learning frameworks (TensorFlow, PyTorch) further enhances the technical scope, making this role highly multidisciplinary.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This role sits at a moderate-to-high difficulty level due to its expectation of production ML experience rather than theoretical knowledge. Candidates must demonstrate hands-on deployment skills, not just model development. The 2–5 years experience requirement narrows the pool but increases expectations around independence and system design. Competition is particularly strong among EU-based engineers with cloud certifications and MLOps exposure.

🚀 Career Impact

This role delivers high long-term career leverage by combining AI engineering with cloud-native deployment expertise. You will build production-ready ML systems, a critical skill gap in the market. The exposure to enterprise clients and cross-functional teams accelerates your path toward AI Architect or ML leadership roles, making it a strong stepping stone in the European AI ecosystem.

📋 Key Responsibilities

You will design, develop, and deploy scalable ML solutions using Google Cloud, ensuring they meet performance, security, and governance standards. A key responsibility is to industrialize machine learning models by integrating them into production pipelines with CI/CD and monitoring systems.

You will also collaborate with Data Scientists and Engineers to build end-to-end data workflows, leveraging SQL, ETL processes, and big data tools. Additionally, you will define best practices for MLOps platforms and AI architecture, while contributing to innovation initiatives, research, and solution design that support business growth.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

This section is personalized by seniority.

How to use: Paste into ChatGPT, Claude, or Gemini

🧠 Fit & Positioning Analysis

Evaluate your match before applying.

📅 Application Signals

This role shows moderate urgency given its consulting nature and ongoing project demand. However, competition is high among candidates with GCP and MLOps experience. Early applicants with strong production ML portfolios will have a clear advantage. Delays may reduce visibility as hiring pipelines fill quickly in consulting environments.

🔗 Apply for this Job

Apply on Company Site

✅ Job Source & Verification

This job posting originates from the official BIP careers platform, ensuring high source credibility and accuracy of role details. The listing was last updated April 2026, indicating an active hiring process. Candidates are advised to verify application status directly on the company site for the most current updates.