SDE II (ML Platform Team)

About the ML Platform Team

The ShareChat Machine Learning (ML) Platform team is responsible for building scalable shared infrastructure that accelerates the pace of ML development and magnifies both the impact and quality of ML use-cases deployed across the company.

About the Role

We are looking for deeply passionate engineers who have demonstrated the ability to design, build, and scale distributed backend services. This role on the platform team offers the opportunity to work on:

• Building out feature computation, storage, monitoring, analysis, and serving systems for billions of features required across ShareChat applications every day.
• Developing distributed real-time training & experiment infrastructure over terabytes of data.
• Developing a highly scalable, high-QPS inference service providing low latency performance using a mix of CPU and GPU hardware to most efficiently utilise resources.
• Scaling distributed backend services to reliably support high-QPS low latency use cases.
• Building core data and model metadata systems powering the end-to-end ML lifecycle.
• Advancing the usage of ML monitoring, observability, and explainability across the company.

To accomplish this, you will make use of cutting-edge open source technologies like Kubernetes, Docker, Golang, Python, Kafka, Spark, Snowflake, Metabase, Tensorflow, and PyTorch among others.

Requirements

• 4+ years of industry experience with a solid understanding of engineering and infrastructure best practices.
• Strong coding skills with Go, Java, or Scala. Familiarity with Python is a plus.
• Hands-on experience using data processing tools like Beam, Spark, Flink, or Storm in a cloud environment like GCP or AWS and first-hand knowledge about data management concepts.
• Experience writing libraries or tools used by other engineers or researchers.
• A keen drive for code quality, reliability, continuous improvement, and monitoring.
• Values team success over personal success.