R&D Intern - Computer Vision

at  Rapsodo

Rapsodo is a Sports Technology company with offices in the USA, Singapore, Turkey & Japan. We develop sports analytics products that are data-driven, portable and easy-to-use to empower athletes at all skill levels to analyse and improve their performance. From Major League Baseball star pitchers to Golf tour players, athletes use Rapsodo technology to up their game across the world. Trusted by coaches and players from youths to professionals, Rapsodo provides real-time insights for all-time performance.
We are innovative, focused, and rapidly growing. We are continuously looking for team players who will stop at nothing to deliver state-of-the-art solutions as part of Team Rapsodo.

REQUIREMENTS

• Pursuing Bachelors or Masters in Computer Science, Software Engineering, AI, or related fields.
• Good communication and organizational skills.
• Critical thinking skills with a detail-oriented mindset.
• Insight into the quality issues in the product life cycle is a plus
• A pro-active, organized & meticulous person who is able to work independently in a fast-paced environment.
• Knowledge in deep learning, convolutional neural networks (CNN) and image processing.
• Strong aptitude to learn and contribute.
• Understanding of QA, with knowledge in designing and executing tests, and reproducing bugs, a plus.
• Programming skills and experience in Python.
• Experience in software and product testing.

• Work with an engineering team on a range of sports product research, design and development
• Assist in developing and maintaining Python console and GUI applications for 3D rendering tools
• Assist to develop tools, test cases and programs to automate process during various stages of product life cycle.
• Develop automated synthetic data generation pipeline using Blender and Python for training of deep learning model
• Help conduct in-office and field experiments to evaluate performance of algorithm in real-life settings.
• Work with Senior Engineers to explore better image processing algorithms to solve problems.
• Perform data analytics.
• Build pipelines for automated data analytics.