Bell Labs AI Research Solutions Intern

Number of Position(s): 2
Duration: 10 Weeks
Date: June 1st to Aug 7th, 2026
Location: Hybrid in Murray Hill, NJ 

EDUCATIONAL RECOMMENDATIONS 

The candidate must be enrolled in the second year of a master’s program or in a doctoral program in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning, or a related field at an accredited college or university within the United States.
 

• AI/ML fundamentals and algorithms: learning strategies, feature engineering, generalized and specialized models 

• Full-stack programming: Python, version control, dashboard, scripting, AI/agentic frameworks

• DevOps for AI/ML lifecycle: Kubernetes, continuous deployment, and training

• The ability to interpret 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

It would be nice if you also had knowledge or experience of one or more of the following:

• Learning architectures, ML model optimization, model drift detection, lifetime learning, knowledge graphs, or world models

• Developing solutions using single or multi-modal data (e.g., vision, text, RF) combined with machine learning to solve interesting problems.

• Wireless or wireline connectivity fundamentals, such as communication theory, networking, or interconnect fundamentals.
   

As part of our team, you will

• Apply research ideas to real-world scenarios under the guidance of experienced mentors.

• Conduct research on novel and existing AI paradigms to address defined problem statements.

• Design and develop high-quality software frameworks and tools for end-to-end AI lifecycles.

• Manage data collection, calibration, and model development for reliable, scalable performance.

• Implement, test, and optimize AI models or agentic workloads for real-time applications.

• Communicate results and insights through reports, presentations, papers, or patents.

• Collaborate across teams to ensure solutions align with deployment, cost, and performance goals.