Staff MLE

Staff Machine Learning Engineer Who are we and What do we doShareChat (https://sharechat.com/about ) is Indias largest homegrown social media company, with 400+ million monthly active users across all its platforms including Moj, a leading short video app which was launched in a record 30 hours. Founded in October 2015, with a vision of building an inclusive community that encourages & empowers each individual to share their unique journey and valuable experiences with confidence. We are spearheading Indias internet revolution by building products through world-class AI & tech to evangelize the content ecosystem for India in regional languages. We believe in complete ownership of problem-solving while committing to speed and integrity in everything we do. We place the utmost importance on user empathy & strive to work towards creating a world-class experience for them every day. Join us to drive how the next billion users will interact on the internet! What does the team doServing recommendations to 300 million users entails developing large scale personalization and recommendation models that not only understand user needs and preferences, but also help 100 million+ creators grow their audiences on our platforms. A subset of the problems we tackle include: Create personalized feeds for 300+ million users via real-time candidate generators, multi-task prediction models, whole-page optimization, and in-session personalization. Nurturing our creator ecosystem, and developing models for strategic content valuation. Multi-objective balancing and long term measurement. We rely extensively on state-of-the-art ML around personalization, deep learning, bandits, causal inference, optimization, ranking and recommendation. What You ll DoWithin the Sharechat AI team, we are looking for an experienced Staff ML engineer to lead the ML efforts around improving personalization models, leading efforts across 10+ MLEs and decision scientists working on feed ranking and candidate generation systems that power Sharechat s recommender systems. In this role you will help us further improve our recommendation systems, and act as a subject matter expert in the recommender systems and ML ranking domains. You would be joining us at an exciting time! The science behind recommendation systems is rapidly changing, and we re making big progress at a rapid pace. Who are youDesign and help develop systems that serve recommendations to over 300 million users Drive ML roadmap creation and execution, specifically around feed ranking and recall oriented candidate generation systems Provide technical guidance in ML model formulation, implementation & experimentation, and take end to end ownership of ML systems, and key user satisfaction based metrics Drive architectural strategy and design for complex ML systems that support the needs of users, creators and content stakeholders Preferred Qualifications Hands-on experience training and serving large-scale models using frameworks such as Tensorflow or PyTorch Experience productionising machine learning models, and managing and designing end to end ML systems, and data pipelines Deep understanding of the mathematical foundations of Machine Learning algorithms Direct experience in building and applying large-scale (100M+ users) machine learning solutions for feed ranking, and personalizing recommendations. You stay up-to-date with the state-of-the-art technology in the domains of recommender systems, data engineering, and machine learning. Relevant publications in top tier applied machine learning conferences is a plus You have a Master s or PhD in ML, statistics, or an engineering field with 5+ years of experience Where you ll beWe are a distributed workforce across Asia and Europe. For this role, we prefer that you are located within India or the EMEA region. We operate within the Indian Standard Time (IST) and GMT time zones for collaboration and prefer that all be located in these time zones. Know more about us: AI @ ShareChat | AI Projects @ ShareChat / Our Blog Whats in it for youAt ShareChat, our values - Ownership, Speed, User Empathy, Integrity, and First Principles - are at the core of our ways of working. We believe in hiring top talent and grooming future leaders by providing a flexible environment to aid growth and development. We also offer several benefits to our employees - like ESOPs, remote working, monthly childcare allowance for women employees, insurance coverage, and more.