Staff Machine Learning Engineer

Who are we and What do we do?

ShareChat is India's largest homegrown social media company, with 325+ million monthly active users across all its platforms including Moj, a leading short video app. Founded in October 2015, we aim to build an inclusive community that encourages individuals to share their unique journeys and valuable experiences. We are spearheading India’s internet revolution by building products through world-class AI & tech to enhance 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 and strive to create a world-class experience for them every day.

What does the team do?

Serving recommendations to 300 million users entails developing large scale personalization and recommendation models that understand user needs and preferences, helping over 100 million creators grow their audiences. A subset of the problems we tackle include:

• Serving personalized feeds for 300+ million users via real-time candidate generators, multi-task prediction models, whole-page optimization, and in-session personalization.
• Nurturing our content and 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 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.

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 8+ years of experience.

Where you’ll be?

Fully remote within the UK or a European time zone.

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, including ESOPs, remote working, monthly childcare allowance for women employees, insurance coverage, and more.