Master Thesis Internship - AI Research Energy Efficiency of Foundation Models

Why join Ericsson? We are a world leader in the rapidly changing environment of communications technology – by providing hardware, software, and services to enable the full value of connectivity. You’ll play a part in using your skills and creativity to push the boundaries of what’s possible. To build never-seen-before solutions to some of the world’s toughest problems. Join a team of like-minded innovators driven to go beyond the status quo to build what’s next.

At Ericsson, you can be an explorer, a change maker and a force for good.
Our purpose: To create connections that make the unimaginable possible.
Our vision: A world where limitless connectivity improves lives, redefines business and pioneers a sustainable future.
Our values: Our culture is built on over a century of courageous decisions, in a place where co-creation and collaboration are embedded in the walls and where our core values of professionalism, respect, perseverance and integrity shine through in everything we do.

About this opportunity

New research works are investigating the best routes to navigate LLM-based models and limit neuron activations for increased efficiency. None have been proposed for foundation models, despite their similarities in architecture. This internship proposal aims to investigate, design and evaluate adaptative routing and gating mechanisms integrated into foundation models. It will explore baseline approaches, proposed for LLMs, then develop hybrid architectures that combine for instance Mixture of Experts layers, learned routers, task-aware controllers, and/or task-based routing to improve efficiency specialization and reduce the carbon footprint of such huge models. The project will investigate different criteria (like sparsity, confidence, and task specificity) and training strategies (supervised and forecasting based on time series data) for such routing mechanisms and evaluate the energy efficiency gain that can be obtained without sacrificing performance and generalization capabilities.

You’ll get the opportunity to

• Test and evaluate different state-of-the-art approaches


• Speed up foundation models, and propose ways to improve their energy efficiency, understanding their strengths, limitations, and applicability to telecom time series data.  


• You'll also have the opportunity to integrate a multinational culture where you can discuss and interact with different skills and backgrounds.

Key skills

• You should be in the final year of a master's program (level 2) or engineering studies (level M2).


• You demonstrate theoretical knowledge and appetence for AI techniques and Machine Learning


• You also have good programming skills, especially in Python.


• Additionally, familiarity with telecommunications is considered beneficial.


• You are fluent in English.

What we offer?At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.

Interns who join us will enjoy an outstanding chance to make connections, to make change, to make a real difference. To put it simply, we change how people, businesses and societies connect – and the results are genuinely exciting, challenging and often, awe-inspiring.
 
What happens once you apply?Click Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.

Primary country and city: France (FR) || Massy

Req ID: 780759