Senior ML Engineer

Nokia

Nokia

Software Engineering, Data Science

Posted on Nov 26, 2025

The Nokia CNS AI R&D (AIRD) team is dedicated to inventing and deploying the next generation of intelligent, generative AI and machine learning technologies that will shape Nokia’s future. This team represents a strategic investment and unification of our AI initiatives—transitioning from isolated features to a cohesive, powerful product and platform portfolio. As a central driver of Nokia’s future growth, AIRD is building a suite of best-in-class technologies recognized across the industry.


As a Senior ML Engineer at Nokia, you will lead cutting-edge research and development of AI solutions that harness the power of Generative AI, intelligent agents, deep learning, and machine learning. Your work will support a wide range of products and platforms—from advanced analytics and cybersecurity to core telecom capabilities. Nokia’s innovation in AI depends on the groundbreaking solutions you will help create.

You Have:

  • 6+ years of relevant machine learning experience.
  • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch), optimization algorithms, deep-learning techniques.
  • Experience with search engines and vector databases, along with their underlying algorithms.
  • Experience with big data frameworks and technologies such as Spark, Kafka, Cassandra.

It would be nice if you also had:

  • MS or PhD in Computer Science or Engineering, Mathematics, or a related field.
  • Prior experience in telecom industry.

  • Design, develop, and deploy advanced AI/ML models and algorithms to analyze and interpret complex data.
  • Design and implement machine learning models to improve a wide range of applications including search, forecasting, text mining and more.
  • Develop and implement agentic-based systems for a wide range of applications including anomaly detection, root-case analysis and more.
  • Optimize existing machine learning models and pipelines for performance, scalability, and resource efficiency.