Grab

Technology

InternDataScientist,GeoMaps

€48–72k ~AI est. Cluj Napoca, Cluj, Romania INTERNSHIP
Market Sentiment
HIGH DEMAND

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optimal for internship candidates.

The Brief

“Intern Data Scientist, Geo Maps at Grab”

Industry & Context.

Technology
Full Job Description

About Grab and Our Workplace Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy. Habits build excellence. We harness the power of Technology and AI to deliver the mission of driving Southeast Asia forward. This mission is about economically empowering everyone with heart, hunger, honour, and humility. Get to Know the Team The Data Science (Geo Vision) team focuses on improving maps and building map-based localization, routing, travel time estimation, and traffic forecasting. These efforts support multiple Grab services. We use a range of techniques, including Computer Vision, NLP, Information Retrieval, Text Mining, and conventional machine learning. These techniques allow us to process a variety of signals, such as images, videos, text, sensor readings, and GPS probes. We use these signals to understand locations and road networks. Get to know the role We are looking for an intern data scientist to help automate the process of map creation using data science techniques. We believe you have at least basic modern vision skills and deep learning knowledge. You will be on site and be reporting to the Senior Engineering Manager based in the Cluj Napoca Office. The Critical Tasks You Will Perform * You will develop architectures to address the latest demands of computer vision and machine learning algorithms. * You will collaborate across DS teams * 3 months internship, 8 hours/day, starting July/August ## Qualifications What Essential Skills You Need * Familiarity with Python and some of the following libraries: PyTorch, Tensorflow or Fast.ai; NumPy; OpenCV; scikit-learn; * Understanding of machine learning methods for classification, regression, and clustering. * Learner who keeps updated with the current state of computer vision and deep learning techniques/architectures. * Proficient in English

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