ShareChat - Staff Machine Learning Engineer - Recommendation System
3 days ago
Who are we and What do we do :
From the humble idea of giving all regional languages a stage to successfully building India's No.1 social media platform, we've journeyed to turn ideas into reality. At ShareChat and Moj, our short video platform ( we have over 325 million users, 80 million creators, and over 2.5 billion shares every month. Valued at $5 billion, ours is a story of disrupting the digital narrative as we build Bharat's content creation ecosystem.
An open, honest culture and our values, such as first principles, speed, integrity, user-centricity, and ownership, drive our teams to innovate our products every day. We are on the path to establishing ShareChat as the world's largest AI-centered social media platform. We are thrilled to offer you the opportunity to solve complex problems at scale, learn with the best minds, pursue unstoppable growth, and most importantly, make a far-reaching impact. Join us to revolutionize Bharat's content creation ecosystem powered by AI & ML. Scaling ideas to
reality is how we do our business
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.
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 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 5+ years of experience
Where you'll be : Bangalore
What's in it for you :
At 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.
"If shortlisted, you will be invited for initial rounds on 29th June in Bengaluru."
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