Lead Machine Learning Engineer

What does the team do?

We serve several hundred million ads daily to our users, sourcing them from both our direct demand and a network of partners integrated via ORTB channels or GAM. Delivering ads at this scale to a diverse user base requires deep neural network (DNN)-based recommendation models, along with a robust infrastructure to support seamless ad delivery.

Beyond recommendation models, our system incorporates a sophisticated marketplace designed to maximize value for advertisers while ensuring optimal budget consumption at a predictable pace. Additionally, it upholds a fair and competitive environment for all partners by ensuring equitable auctions for each ad slot.

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 hiring an Lead MLE to drive the development of cutting-edge ads prediction models. This IC role is central to our Ads team and will focus on end-to-end ownership of core ML modeling - training, deploying, and improving models that predict key user actions such as clicks, installs, and deeper funnel events like transactions. Beyond this, there are exciting opportunities to deploy ML in the ADs ecosystem like on the network ADs side of things as well as on balancing ad revenue with regression in user experience. This is a high-impact role with direct revenue implications, where experimentation success rates are significantly higher due to our dynamic and fast-paced environment. 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
• 4 or more years of experience with a Bachelor’s Degree, Master’s / Phd in a related field (game theory / robotics) is a plus

Where you’ll be?

Bangalore