INTERNSHIP DETAILS

Working Student - Machine Learning/Agentic Systems

Companyramblr.ai
LocationGartenstadt
Work ModeOn Site
PostedMay 8, 2026
Internship Information
Core Responsibilities
Contribute to the design, deployment, and improvement of physical AI systems using multiple machine learning models and (V)LLMs. Focus on extracting deep context from egocentric videos to provide actionable insights for the physical world.
Internship Type
working student
Company Size
Not specified
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About the Role

ramblr

Actionable Insights with Industrial-Grade Video Understanding

AI for the Physical World. At Ramblr, we go beyond superficial video analysis to extract deep context from egocentric videos. Our technology provides a comprehensive understanding of actions, individual objects, and their relationships. Prompt Ramblr’s AI assistant to unlock precise insights and pinpoint specific moments in thousands of hours of multimodal videos captured from a first-person perspective, or find explanations and patterns in your videos you were not aware of. 

Are you excited to become a Ramblr and join us at the intersection of AI and the physical world? If so, you can apply directly to the job posting or use the open application form.

We look forward to hearing from you !

Job Description

We are looking for a Working Student with a strong discovery and engineering mindset for AI and Machine Learning with experience in the usage of deep learning models as part of agentic/complex systems. You will contribute to the design, deployment, and improvement of physical AI systems leveraging multiple machine learning models in conjunction with (V)LLMs.

Your profile

- Profound knowledge in collaborative software development in Python: Follow consistent style-guide, clean design-patterns, write self-documented code
- Familiarity with multisensor datasets and scientific methods for their leverage

- Knowledge of agentic systems and their inner workings. Ideally, experience in their integration and design at multiple levels
- Machine Learning (ML):
  - Ability to use PyTorch or Tensorflow, basics of neural network architectures (Transformer/CNN), model training
  - 
Knowledge of classical ML methods: Unsupervised clustering, Gradient Boosting, SVM
- General: git VCS, code reviews, development on Linux, distributed computing concepts

Education:
- B.Sc./M.Sc. in Computer Science, Physics, Mathematics, Robotics or a related quantitative field.

Why us?

  • Join a highly motivated team with super smart people in a well-funded, early-stage startup
  • Take part in an incredible journey with very competitive salary
  • Become part of an international crew of experienced entrepreneurs and AI luminaries
  • Enjoy full responsibility for your tasks and your work area
  • Come have fun with us, learn from your mistakes and bring good vibes!

About us

Founded by experienced tech entrepreneurs and deep-learning scientists with proven track records, we have embarked on a mission to bring AI to the physical world and unlock next-gen intelligent AR/XR devices. 
Key Skills
PythonPyTorchTensorflowTransformerCNNUnsupervised ClusteringGradient BoostingSVMGitLinuxDistributed ComputingDeep LearningMachine LearningAgentic SystemsVLLMsMultisensor Datasets
Categories
TechnologyEngineeringSoftwareData & AnalyticsScience & Research
Benefits
Competitive SalaryInternational TeamHigh Level Of Responsibility