Job Description
Actionable Insights with Industrial-Grade Video UnderstandingAI 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. Are you excited to become a Ramblr and join us at the intersection of AI and spatial computing? If so, you can apply directly to the job posting or use the open application form.We look forward to hearing from you !We are looking for an Intern/Working Student with strong background in Python and Machine Learning, who can develop, deploy and maintain state-of-the-art models. You will support us throughout the whole ML-lifecycle from understanding data over building ML models to deploying models and monitoring results.Your Profile:- Profound knowledge in collaborative software development in Python: Follow consistent style-guide, clean design-patterns, write self-documented code- Experience with scientific Python libraries such as: numpy, matplotlib, scipy, scikit-learn, scikit-optimize, pandas, seaborn- Proven ability to extract knowledge and understanding from data- Machine Learning (ML): - Ability to use PyTorch or Tensorflow, basic of neural network architectures (Transformer/CNN), model training - Classical ML algorithms: Unsupervised clustering, Gradient Boosting, SVM, ...- General: git VCS, code reviews, development on Linux, distributed computing conceptsEducation:- B.Sc./M.Sc. in Computer Science, Data Science, Physics, Mathematics or a related quantitative field.
We are building an AI-driven data pipeline to unlock next-gen Augmented Reality. In pursuit of this mission, we are leveraging cutting-edge computer vision and deep learning. We are continually searching for new ramblrs for our offices in San Francisco and Munich or even remotely based.
