About this opportunity:

We are now looking for creative, upbeat, out of the box individuals with strong coding and cloud deployment skills to join Engineering Unit Cloud RAN. You will work with senior researchers in Generative AI, data and LLM using Ericsson provided state of the art lab with full access to GPUs, needed data and flexibility to deploy and test high intensity self built applications. Cloud RAN leads the acceleration and creation of a cloud-native Radio Access Network (RAN) product offering with customer deployments. The unit consists of development functions covering the total life-cycle capability from architecture definition to deployment in customer networks & capability to contribute to open source communities, in this ecosystem, industrializing of Cloud Platform services and defining Security in the Radio Access Network is vital 

What you will do:

This thesis work will explore how Generative AI, data insights, and Large Language Models (LLMs) can reshape cloud platform testing by aligning technical goals with business priorities. Key challenges include automating large-scale testing frameworks, creating adaptive testing strategies, and using data and LLMs to optimize capability planning, define risk-based deployment strategies and standardize and industrialize operations. 

Beyond technical efficiency, this research will tackle security gaps, elevate test tool usability, and nurture collaborative, innovative team dynamics. By embedding Generative AI into metrics visualization, vulnerability management, and continuous improvement, the study aims to craft secure, scalable, and forward-thinking solutions for modern cloud platforms

The skills you bring:

For a generative AI and LLM thesis student, key skills include expertise in cloud computing, specifically strong coding skills to work with system comprehension lab and knowledge of deploying CNS on high-power GPUs. Demonstrated skills working with platforms like AWS and Google Cloud and advanced practical knowledge of Kubernetes, containerization, and cloud-native architecture is expected. Strong data engineering skills are essential for pipeline automation and large-scale data handling, along with familiarity of distributed frameworks (e.g., Spark, Hadoop). Additionally, proficiency in MLOps and industry latest tools like Snowflake, Databricks is an asset. 

Understanding LLMs, NLP, and generative modelling techniques, alongside AI product lifecycle knowledge, is critical. Strong communication, personal drive and ability to define and deliver on project timelines with minimal coaching is expected. Continuous learning of AI advancements, especially in ethics and biases in LLMs, is also valuable for success in a rapidly evolving field. This skill set is a pre-requisite for impactful research and practical deployment of AI technologies

Why join Ericsson?

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.
 
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: Sweden (SE) || Stockholm

Req ID: 756075