AI Model Lifecycle Researcher
3 days ago
We challenge ourselves to create an inclusive way of working where we are open to new ideas, empowered to take risks and fearless to bring our authentic selves to work.
The team you’ll be part of
Strategy & Technology
Strategy and Technology lays the path for Nokia’s future technology innovation and identifies the most promising areas for Nokia to create new value. We set the company’s strategy and technology vision, offer an unparalleled research foundation for innovation, and provide critical support infrastructure for Nokia.
What you will learn and contribute to
Lead the development and implementation of standardized practices for managing the lifecycle of machine learning models, specifically focused on user equipment in telecommunications environments.
Oversee the entire AI model lifecycle, including data collection, model training, evaluation, deployment, monitoring, and retraining, ensuring alignment with Nokia's strategic technology vision and objectives.
Develop and implement MLOps best practices, ensuring seamless integration, retraining, and deployment processes that keep AI capabilities cutting-edge and aligned with telecommunications industry research.
Collaborate with cross-functional teams, including data engineers, data scientists, and business stakeholders, to identify opportunities where AI solutions can drive innovation, improve standardization, and contribute to business success.
KEY SKILLS AND EXPERIENCE
You have:
A background with a Master’s or Bachelor’s degree in Computer Science , Data Engineering , Telecommunications , or a related field, with a minimum of 4-10 years of experience .
Proven experience in managing the lifecycle of machine learning models , including development, deployment, monitoring, and retraining.
Strong understanding of MLOps , machine learning workflows, and model monitoring frameworks.
Experience in managing models specifically for user equipment in telecommunications environments.
It would be nice if you also have:
Familiarity with standardization documents from bodies such as 3GPP , ETSI , ITU , and IEEE .
Experience in wireless or embedded systems .
Understanding of data governance and model ethics to ensure responsible AI practices.
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