Senior Backend Engineer

About the Job

The new SaaS will include our recently released Automatic Extraction which provides an API for automated e-commerce and article extraction from web pages using Machine Learning. Automatic Extraction is a distributed application written in Java, Scala and Python; components communicate via Apache Kafka and HTTP, and orchestrated using Kubernetes.

As a Senior Backend Engineer, you will be designing and implementing distributed systems: large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc. - this is going to be a challenging journey for any backend engineer!

Roles & Responsibilities:

• Work on the core platform: develop and troubleshoot Kafka-based distributed application, write and change components implemented in Java, Scala and Python.
• Work on new features, including design and implementation. You should be able to own and be responsible for the complete lifecycle of your features and code.
• Solve distributed systems problems, such as scalability, transparency, failure handling, security, multi-tenancy

Requirements:

• 3+ years of experience building large scale data processing systems or high load services
• Strong background in algorithms and data structures.
• Strong track record in at least two of these technologies: Java, Scala, Python, C++. 3+ years of experience with at least one of them.
• Experience working with Linux and Docker.

• Good communication skills in English.
• Computer Science or other engineering degree.

Bonus points for:

• Kubernetes experience
• Apache Kafka experience
• Experience building event-driven architectures
• Understanding of web browser internals
• Good knowledge of at least one RDBMS.
• Knowledge of today's cloud provider offerings: GCP, Amazon AWS, etc.
• Web data extraction experience: web crawling, web scraping.
• Experience with web data processing tasks: finding similar items, mining data streams, link analysis, etc.
• History of open source contributions