Skip to content
Huawei logo

Intern/Master Thesis Student for Safe Generative AI

Huawei2 months agoWorking Student
On-siteEnglish requiredTechAI, ML & Data Science

Required skills

ProbabilityVision TransformersDiffusion TransformerStatisticsLarge Language Models (LLMs)PyTorchPythonJAXLinear AlgebraMachine LearningDeep Neural NetworksCalculus

Job description

Huawei posted this role. Below, we break down what it means for a working student in Munich: your weekly hours, take-home pay and visa limits. You can also open ChatGPT or Claude with a ready-made prompt to tailor your CV, check your fit, draft a cover letter or prep for the interview.

Jobscan

Will your CV clear this job's ATS filter? Scan it against this job with Jobscan

Description provided by Huawei

Huawei is a leading global information and communications technology (ICT) solutions provider. Our ICT solutions, products and services are used in more than 170 countries and regions, serving over one-third of the world's population. With 197,000 employees, Huawei is committed to develop the future information society and build a Better Connected World.

Huawei's Heisenberg Research Center in Munich is responsible for advanced technology research, architectural development, design and strategic engineering of our products.

Join us as a

Research Intern/Master Thesis for Safe Generative AI (m/f/d)

We are seeking a highly motivated and skilled Research Intern to join our dynamic team, focusing on the safety of generative AI,e.g. Large Language Models (LLMs). This internship offers a unique opportunity to contribute to cutting-edge research in the field of artificial intelligence, specifically in understanding, improving, and evaluating the reliability and robustness of the latest generative AI models.

Your mission

  • Conduct comprehensive research on generative AI safety with a focus on assessing, enhancing, and validating their reliability and robustness in various applications.
  • Develop and implement innovative methodologies to test LLM reliability under diverse conditions and datasets.
  • Collaborate closely with a multidisciplinary team of researchers, data scientists, and engineers to integrate findings into the development of more reliable LLM frameworks.
  • Analyze and interpret complex data sets, utilizing advanced statistical and machine learning techniques to understand model behaviors and identify potential reliability issues.
  • Stay abreast of the latest advancements in Safe AI for DNN, Vision Transformers (ViT), and Diffusion Transformer (DiT) etc., applying this knowledge to improve LLM reliability.
  • Prepare detailed reports and presentations on research findings for both technical and non-technical audiences, contributing to research papers, patents, and other publications as required.

Your areas of expertise

  • Currently enrolled in a Master's or PhD program in Computer Science, Artificial Intelligence, Machine Learning, or a related STEM field, Bachelor students with excellent academic records will also be considered.
  • Solid understanding and hands-on experience with Deep Neural Networks (DNN), Vision Transformers (ViT), Data-Intensive Text (DiT), and other advanced AI/ML models.
  • Strong foundation in the mathematical principles of learning, including but not limited to statistics, probability, linear algebra, and calculus.
  • Proven ability to conduct independent research and problem-solving skills in the field of AI and machine learning.
  • Proficient in programming languages commonly used in AI research such as Python, and familiar with AI/ML frameworks like JAX or PyTorch.
  • Excellent communication skills, with the ability to present complex technical information clearly and concisely.
  • Demonstrated ability to work collaboratively in a team environment and to engage with external research communities.

By applying to this position, you agree with our RECRUITMENT PRIVACY STATEMENT. You can read in full our recruitment privacy statement via the link below.

http://career.huawei.com/reccampportal/portal/hrd/weu_rec_all.html

Your rewards of working here

  • Our culture is characterized by innovative power and team spirit as well as the intensive exchange of knowledge and experience within our global network.
  • We offer healthy meals ranging from traditional Chinese to western delicacies in our famous company canteen.
  • To keep your development ongoing, you will find a broad range of training opportunities. Many online and face-to-face training programs incl. language courses in German and Mandarin.
  • Our diverse and welcoming environment is shaped by different backgrounds and around 40 individual nationalities.
  • Self-responsible work in a competent, motivated and constantly growing team.

Please send your application and CV (incl. cover letter and reference letters) in English.

Working student essentials

What this Tech working student role in Munich means for you: the weekly-hours rules, the social-contribution perks, and what international students should check before applying.

Weekly hours

Working students may work up to 20 hours a week during the semester and full-time during the breaks. Staying within this keeps your student status and the Werkstudent benefits.

Working student rules

Social contributions

Under the Werkstudentenprivileg you're exempt from health, care and unemployment insurance contributions — only pension insurance applies. That leaves more net pay than a regular job.

Check your insurance

International students

Non-EU students can work 140 full or 280 half days per year (raised from 120/240 in March 2024). A working student contract usually fits within this — confirm the exact limits printed on your residence permit.

Studying in Germany

Frequently asked questions

Similar jobs