Staff MLE

What does the team do?

Serving 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.

AI - Our AI teams are spearheading the research and development, presenting innovations at various conferences. to learn. 

Learn from our CEO Ankush about our culture, innovation and growth..

What You’ll Do? 

Within 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 you?

Design 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 be?

Bangalore 

Why join ShareChat?

We believe in creating economic opportunities for our content creators as a shared purpose. Join us to make a tangible impact for regional Indian audiences.  Grab an opportunity to solve complex problems powered by our AI and ML recommendation system for over 325 million monthly active users, 80 million creators and key partners.  Drive your career growth through our upskilling programs, accelerated by values like speed and ownership. You get a chance to work with top talent across the globe in a collaborative and learning culture.  Experience growth in a people-first organisation with unparalleled rewards and employee-centric policies, including ESOPs, monthly childcare allowance, insurance, and more.

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