Staff MLE

What Youll 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 Sharechats 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 were 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 Masters or PhD in ML, statistics, or an engineering field with 8+ years of experience

Where youll be? Bangalore