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. 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 ! Job Description We are looking for a strong deep learning scientist who can develop and monitor state-ot-the-art AI models. You quickly and efficiently probe and evaluate deep learning models for new use cases and help bring them into production. You quantitatively evaluate the performance of models and optimize the interplay between different components of our deep learning stack. You work closely at the intersection of research and product development. You are a key player in extending our offering for internal use and customer use-cases - field testing and iterating quickly. Your profile Passion for solving the hard problems in deep learning Required: Data driven QA: definition of useful metrics, implementation of processes to measure metrics, data visualization Machine Learning: model analysis, data loading pipelines, data monitoring, neural network architectures (especially Transformer / CNNs), model training, PyTorch Computer Vision: CNNs, Vision Transformers, spatio-temporal data, image- and video embeddings, image augmentation Experience with scientific python libraries such as: numpy, openCV, matplotlib, scipy, scikit-learn, scikit-optimize, pandas, seaborn General: git VCS, code reviews, development on Linux, distributed computing concepts Proficiency in python-based collaborative software engineering: follow consistent style-guide, clean design patterns, self-documented code, unit/integration tests, type annotations Optional: Natural Language Processing: Transformer architectures, vision-language alignment, prompt engineering Video understanding: Action understanding, activity prediction, scene graph prediction Computer vision: GANs, image morphology, optical flow, depth/3D reconstruction Ability to apply classical machine learning algorithms such as boosted trees, clustering and alike Acceleration in python: numba, c++/CUDA extensions, cython, PyTorch c++/CUDA extensions, ONNX, TPUs Education M.Sc./Ph.D. in computer science, physics or mathematics with focus on computer vision, machine learning or a related field 3 years of relevant work experience Fluent in English Why us? Join a highly motivated team with super smart people in a well-funded, early-stage startup Take part in an incredible journey and participate in our equity incentive plan Become part of an international team of experienced entrepreneurs and deep-learning experts Play a decisive role in shaping a company with a creative working environment and streamlined decision-making 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.