PpWorking at Sky Italy in Data Platform Analytics (DPA) is a unique opportunity to shape the best solutions to unlock the full value of data by adopting advanced analytics and derive knowledge to gain insights on how to keep our customers experience at top level. /p h3Overview /h3 pAs a SeniorMachine Learning Engineer, you will play a strategic and hands-on role in designing, building, and scaling Machine Learning solutions within the DPA area. /p pYou will contribute the evolution of advanced analytics across our Data Platform by championing modern ML approaches, strengthening end-to-end ML infrastructure, and accelerating the adoption of Big Data and GenAI capabilities. /p pThis role blends deep technical expertise with leadership influence and you will help shape the ML vision, ensure scalability, and deliver measurable business impact through production-ready ML/AI initiatives. /p h3Responsibilities /h3 ul liContribute to the execution of the AI/ML strategy aligned with business priorities, identifying and prioritizing high-impact use cases and translating them into scalable, production-ready solutions /li liLead the technical roadmap and evolution of the end-to-end ML platform, ensuring robust architecture, strong MLOps practices, and full lifecycle governance (development, deployment, monitoring, retraining, compliance) /li liDrive the adoption, experimentation, and industrialization of ML solutions across relevant business domains /li liEnsure production systems meet enterprise standards for scalability, reliability, security, and regulatory compliance, while continuously monitoring model performance and business KPIs /li liContribute to the growth of ML engineering capabilities by mentoring junior team members and collaborating effectively with senior technical and business stakeholders to foster innovation and engineering excellence /li /ul h3Skills Requirements /h3 ul liProven experience designing, deploying, and scaling ML systems in production environments. /li liStrong expertise in ML frameworks, distributed systems, data modeling, and cloud-native software architecture /li liSolid hands-on experience with MLOps practices, CI/CD pipelines, infrastructure automation, monitoring, and ML lifecycle management /li liExperience working with large-scale structured and unstructured datasets within Big Data ecosystems /li liAdvanced proficiency in Python and core ML/data science libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow) /li liStrong foundation in mathematics and statistics, combined with strategic thinking, stakeholder engagement, and leadership capabilities /li /ul h3Experience Education /h3 ul li5+ years of experience in Machine Learning / AI / Data Science, with proven hands-on production experience /li liMaster’s degree in Computer Science, Engineering, Mathematics, or a related quantitative field /li liProfessional proficiency in English /li /ul /p #J-18808-Ljbffr