Working Student - Machine Learning/Deep Learning at ramblr.ai

Gartenstadt, Bavaria, Germany -

Full Time

Start Date

Immediate

Expiry Date

06 Aug, 26

Salary

0.0

Posted On

08 May, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, PyTorch, Tensorflow, Transformer, CNN, Unsupervised Clustering, Gradient Boosting, SVM, Git, Linux, Distributed Computing, Deep Learning, Machine Learning, Agentic Systems, VLLMs, Multisensor Datasets

Industry

Description

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.

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.