Full Stack Developer - Recommendation Team Job in Pratilipi

About Company: Pratilipi has 20M+ monthly active users and 2M+ daily active users, and we aim to be impacting over 500M+ users in near future.
We are looking for Software Engineers that can build services, features, use-cases in a fast paced environment, while improving the performance of our systems as we rapidly scale our product and organization and delight our users.

About the Team: Our Engineering team works closely with the Product, Business and Data Science teams to build experiments & features that enable delightful experiences for our Users. We're a small team that learns from each other and iterates rapidly to make a larger impact. Our Micro-services architecture allows us to be Polyglot in technology stack. We are completely hosted on AWS Platform. We are available to users via Web, Android and iOS. We work in a high ownership, high responsibility environment.

Our Tech Stack:
stackshare.io/pratilipi/pratilipi

Glimpse of our scale:

• 2M+ DAU
• 20M+ MAU
• 1.3+ billion requests per day spread cross 40+ micro-services
• resting around 10TB of data
• daily ingestion of 500GB data

Key Responsibilities:

• Work closely with Software Engineers and Data Scientists to build data infrastructure that fuels the need of personalisation/discovery team.
• Build robust, secure and scalable micro services to power the Personalisation Engine at Pratilipi.
• Build click stream processing pipelines to compute personalisation recommendations for our users in real time.
• Automate and optimise manual processes for data extraction and delivery required for a wide variety of use-cases from analytics to recommendations.

Requirements:

• High speed of execution
• Excellent problem solving skills
• Highly dedicated and a good team player
• Willing to take risks and willing to fail doing that

Pluses:

• Experience with Redis, Cassandra
• Experience in Apache Spark, Hadoop
• Experience in building distributed domain driven micro services
• Interests in Machine Learning