Logga in
Sök med AILogga in
JobbSafariLediga jobbMaster thesis:Custom LLM Development

Master thesis:Custom LLM Development

Ericsson AB
Ny

Sammanfattning

Ericsson is seeking master's thesis students for two projects focused on enhancing a specialized language model for Ericsson's Many-Core Architecture (EMCA). The work will take place at the System Comprehension Lab in Kista, Sweden, where students will have access to advanced training resources. The projects involve addressing catastrophic forgetting during model training and integrating reasoning capabilities with external tools to improve coding efficiency for EMCA tasks.
Visa hela jobbannonsen

Det här erbjuder vi

Access to training pipelines, GPU resources, and evaluation suites.Opportunity to work on cutting-edge AI projects in a collaborative environment.Experience in a diverse and inclusive organization that values innovation.

Stockholm

Ansök senast: Öppet tillsvidare
Publicerad: 2026-09-18

Beskrivning

Join our Team

About this opportunity

AI coding tools like Claude Code, Kiro, or Codex have become indispensable to most developers. At Ericsson, many developers work with a C-like programming language customized to program Ericsson's own silicon - Ericsson's Many-Core Architecture (EMCA). Because this language is not represented in the training data of general-purpose LLMs, coding assistance for EMCA can be inefficient, both in terms of token consumption and output quality.

At Ericsson's System Comprehension Lab, we are training an in-house language model on EMCA source code to serve as a specialized tool for an orchestration agent. We are recruiting for two related master's thesis opportunities in this area: one on mitigating catastrophic forgetting during continued EMCA-specific training and one on tool-integrated reasoning. Both projects aim to improve the model's usefulness for EMCA development.

Please indicate in your application which project you are most interested in. The exact focus of each project will be refined together with the student based on their interests, background, and the state of the model training team's research when the project starts. The work will be carried out with the team in Kista. You will have access to training pipelines, GPU resources, evaluation suites, and coding assistants such as Claude Code.

What you will do

Direction 1: Mitigating Catastrophic Forgetting

The model has general capabilities, such as instruction following and broad coding knowledge, acquired during its original pre-training. At Ericsson, we adapt it to EMCA through continued pre-training and supervised fine-tuning on EMCA data. Additional EMCA-specific training may cause catastrophic forgetting: the model may improve on EMCA tasks while losing some of those general capabilities. This project investigates methods to improve EMCA-specific performance while preserving these capabilities.
  • Establish a baseline using the current continued-pre-training and supervised-fine-tuning approach
  • Implement and evaluate methods such as self-distillation, curriculum learning, model merging, or related techniques
  • Measure both gains in EMCA-specific knowledge and retention of general capabilities, including instruction following and broad coding skills


Direction 2: Tool-Integrated Reasoning

This project explores how to extend the model with reasoning and tool interaction, potentially using reinforcement-learning-based training. Tool-integrated reasoning allows the model to invoke external tools and use their feedback during problem solving, with the aim of improving code accuracy and efficiency for complex or abstract EMCA tasks.
  • Establish a baseline using the current model and standard reasoning methods
  • Design, implement, and evaluate methods that enable the model to decide when to invoke tools - such as code execution, graph traversal, or vector search - interpret their feedback, and correct its reasoning when needed
  • Assess improvements in EMCA task performance, code accuracy, tool-use effectiveness, token efficiency, and the ability to handle more abstract queries


The skills you bring

  • You are pursuing a master's degree in computer science, engineering mathematics, physics, or a related field
  • Good understanding of modern AI and machine learning, particularly generative AI and large language models
  • Strong programming skills and an interest in experimental, research-oriented work
  • Familiarity with deep-learning frameworks such as PyTorch
  • Previous experience with LLM fine-tuning is a plus
  • You are analytical, curious, and able to work independently while communicating your results clearly


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: 790807

Ansök till tjänsten

Master thesis:Custom LLM Development

Ny
Denna arbetsplats har annonserats på Ericsson-tjänsten den 2026-09-18 och publicerades av Ericsson.
Tillbaka till toppen

OM FÖRETAGET

Ericsson AB
Visa alla jobb för Ericsson AB

Hittade du inte vad du letade efter?

Beskriv med dina egna ord vad du söker, precis som om du skulle förklara det för en kompis. Josi hittar jobb som matchar dig på riktigt.
Testa nu

Sök efter fler liknande jobb

StockholmForskning och utvecklingThesis workBachelor's ThesisMaster's Thesis

Läs också

Efter vårens uppgång – jobbannonserna minskar igen
För arbetsgivare

Efter vårens uppgång – jobbannonserna minskar igen

Antalet jobbannonser i Sverige ökade i juni för andra månaden i rad, vilket visar en fortsatt positiv trend på arbetsmarknaden.

Lästid 3 min

Liknande jobb

Visa alla lediga jobb
Scania Group

Master Thesis Student

Södertälje
2/9 – tillsvidare

Jobb per stad

Det är enklare än någonsin att söka jobb – men svårare än någonsin att hitta rätt. Det vill vi ändra på. JobbSafari är din guide genom arbetslivet, byggd för att matcha rätt person med rätt möjlighet bland tusentals lediga jobb i Sverige.

JobbSafari är en del av Duunitori Group – Duunitori är Finlands största jobbsökmotor och en betrodd partner inom rekrytering, rekryteringsmarknadsföring och employer branding.

Stockholm, Sweden

JobbSafari AB

Grev Turegatan 11A

114 46 Stockholm, Sweden

info@jobbsafari.se

+46 (0) 8 515 10 774

Helsinki, Finland

Duunitori Oy

Toinen Linja 7

00530 Helsinki, Finland

asiakaspalvelu@duunitori.fi

+358 44 980 3558

Oslo, Norway

JobbSafari AB

c/o Accountor AS

Tangen 75

4608 Kristiansand, Norge

info@jobbsafari.se

+46 70 314 59 79

  • jobbsafari.se
  • duunitori.fi
  • jobbsafari.no
  • allaloner.se
  • jobbland.se