Senior Software Engineer, Video Understanding
1. Engineering – Video
About the Role
At Hotstar, we have over 100 million users and capture close to a billion click-stream messages daily. The engineering team at Hotstar is at the centre of the action and is responsible for creating unmatched user experience. Our engineers solve real life complex problems and create compelling experiences for our customers.
Every day, massive amounts of video are uploaded into Hotstar services. In order to serve our communities better, it is critical that we can understand this content; think about being able to answer questions like "This person will like this video because...." or "This person will find this video inappropriate because.Our goals broadly encompass content understanding, including the ability to produce video summaries, categorize content according to topic and purpose, identify audio events,find region of interest in a video scene, converting 16:9 videos to portrait full screen keeping maximum context of video. To achieve these goals, we are building a Video Understanding team in Bangalore, that will engage in a multidisciplinary effort combining speech recognition, natural language processing, and image processing. We view video as inherently multi-modal content, and seek to develop methods that use all the information available. We are looking for researchers in machine learning and AI with strong software engineering skills, and a desire to build systems that will ship to billions of people.
The pace of our growth is incredible – if you want to tackle hard and interesting problems at scale, and create an impact within an entrepreneurial environment, join us!
Your Key Responsibilities
- Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies
- Conduct research to advance the state-of-the-art,and publish work in relevant speech, NLP, and machine learning conferences and journals
- Apply expert coding skills to projects in partnership with other engineers across research, product, and infrastructure teams
- Adapt machine learning and neural network algorithms for training competitive, state-of-the-art models which make the best use of modern parallel environments (e.g. distributed clusters, GPU)
What to Bring
- MS degree in Computer Science or related quantitative field with 5+ years of work experience, or Ph.D. degree in Computer Science or related quantitative field
- Knowledge of machine learning, neural networks, and deep learning
- Experience building systems based on machine learning and/or deep learning methods, especially in the areas of speech recognition, natural language processing, image processing, or other machine-perception tasks
- Experience developing and debugging in C/C++ and/or Python
To learn more about our team , check out the following articles :