Principal AI Engineer

Overview

As a Principal AI Engineer at Nokia, you will architect and lead the next generation of AI solutions that power Nokia's wide range of products & platforms – from analytics to security to telecom core capabilities – by employing the latest techniques – from reinforcement learning to generative AI to large-scale deep learning models. You will design strategies for holistic optimization of Nokia's CNS ecosystem across all product touch points to create a cohesive, highly value-driven technology innovations for our customers. Nokia relies on innovative AI research and applications that you will help us build. As a key leader in the organization, you will lead research, design algorithms, build software, anticipate and influence the state of the art in the industry, and leverage and create open-source software in the process. Responsibilities

Architect, design, and execute the technical roadmap for AI initiatives, directly contributing to Nokia’s CNS key product portfolio. Set the technical direction and provide mentorship to a high-performing team of 20+ machine learning and software engineers, fostering a culture of innovation and high-impact execution Influence the technical direction of the broader engineering organization by establishing best practices and mentoring senior engineers Drive technical excellence in building scalable, reliable, and cutting-edge ML systems, tackling the most ambiguous and complex problems Partner closely with leaders in cross-functional teams to deliver on a shared vision of an AI-driven telecom product portfolio Qualifications

You Have: 10+ years experience in building engaging AI-powered consumer products at scale, with at least 5 of those years in a technical leadership position Experience leading technical projects with multiple stakeholders Experience in designing and optimizing recommender systems that create highly personalized experiences for LinkedIn’s members and scale to solve complex business problems Experience in leading large scale development projects from concept to multiple releases in production Experience of technical leadership guiding and mentoring engineering and operations talent Experience leading high-impact, cross-company initiatives It would be nice if you also had: PhD in a relevant field or related discipline (machine learning, statistics, computer science etc.), or equivalent applied R&D experience.

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