Position: Applied AI/ML Research Solutions Intern
Number of Position(s): 3
Duration: 10 weeks
Date: June-August 2025
Location: Onsite

 

The team you'll be part of

Nokia Bell Labs is Nokia's world-renowned research arm. It has invented many of the foundational technologies that underpin information and communications networks and all digital devices and systems. This research has produced nine Nobel Prizes, five Turing Awards, and numerous other awards.

The AI Accelerator Group at Nokia Bell Labs is developing state-of-the-art artificial intelligence-based solutions focused on using computer vision and natural language processing to understand physical spaces in space-time, exploring generalizable learning models and optimization techniques for real-time performance. 

 

EDUCATIONAL RECOMMENDATIONS

Currently a candidate for a Master’s, or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning, or a related field within an accredited school in the US. 

The ability to understand and communicate key underlying ideas, concepts, and associated problems in complex research papers and system reports. Willingness to contribute with creative, out-of-the-box solutions, to problems arising in a dynamic environment Some experience with AI/ML and competency in one or more programming languages (Python, Matlab, etc) and frameworks such as Pandas, Keras, TensorFlow, or PyTorch.

It would be nice if you also had:

Knowledge of deep learning neural network architectures, ML model optimization, localization and tracking techniques, scene graphs, and world models Experience in developing solutions applying computer vision or natural language processing concepts combined with machine learning to solve interesting problems. Familiarity with Docker-based microservices and Kubernetes

 

As a part of our team, you will: 

Get exposure to the challenges faced in applying research ideas to real-world problems, experience the thrill of performing experiments under the guidance of experienced mentors, and develop solutions at a fast pace to meet your goals.

Depending on the intern’s interest and academic/research experience, interns will have a chance to partake in one or both domains mentioned below. The specific topic will be assigned depending on the need:

Vision-based perception and reasoning systems for physical-digital fusion including localization, tracking, and building scene graph-based world models. Natural language processing-based personalized systems for space-time understanding and contextual awareness.

All work would be candidates for integration into larger in-use systems and therefore need to consider cost, ease of deployment, and real-time performance during the internship.