Staff Software Engineer in England

ShareChat (Mohalla Tech Pvt Ltd) is India’s largest homegrown social media company and the only local player to achieve profitability in the industry, with 200+ million Monthly Monetizable Users across all its platforms. Founded in 2015, ShareChat has social media brands such as the ShareChat App and Moj App and micro drama app QuickTV under its portfolio. QuickTV, the newest addition to ShareChat's family of apps, crossed the 10 million downloads mark within 3 months of launch and currently has 60Mn MAUs across the network viewing the vertical episodic content.

Today, the ShareChat network maintains a whopping 1,000 Cr ARR and is India’s leading social media platform servicing users across the country in 15 regional languages. Serving recommendations to 300+ million users entails developing large scale personalization and recommendation models that understand user needs and preferences in real-time, while also helping creators grow their audiences on our platforms. Nurturing our content and creator ecosystem, and developing models for strategic content valuation.

We rely extensively on state-of-the-art ML around personalization, deep learning, causal inference, optimization, ranking and recommendation. Within the Sharechat AI team, we are looking for an experienced Staff engineer to lead the engineering efforts around serving personalization models efficiently at scale, leading efforts across 10+ MLEs, SDEs 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 in order to drive up user retention and engagement while minimizing server and cloud costs of serving large scale models, and act as a subject matter expert in the recommender systems and ML ranking domains.

• 8+ years of industry experience with a solid understanding of engineering, infrastructure and ML best practices.
• Strong coding skills with Go or JAVA.
• Design and help develop systems that serve recommendations to over 300 million users.
• Provide technical guidance in ranking systems design, 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.
• Familiarity with cloud platforms such as AWS, Google Cloud, or Azure.
• Experience designing end to end ML data pipelines.
• Experience with database technologies such as PostgreSQL, MySQL, or MongoDB, Spark, Databricks and stream data processing such as Kafka, RedPanda is a plus.
• Direct experience in building and applying large-scale (100M+ users) machine learning solutions for personalizing recommendations.
• Hands-on experience building training frameworks and/or serving large-scale models using tools such as Tensorflow or PyTorch is a plus.
• You stay up-to-date with the state-of-the-art open source infrastructure solutions applicable to designing and improving large scale recommender systems, data engineering, and machine learning.
• You have a Master’s or PhD in Computer Science, statistics, or an engineering field with 5+ years of experience.

London (Remote) We believe in hiring top talent and grooming future leaders by providing a flexible environment to aid growth and development.