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Udemy is looking for a senior software engineer to join our Recommendations Team. Udemy’s personalized recommendations system is composed of batch (e.g., feature and machine learning pipelines), streaming (i.e., feature computation in real-time), and online (i.e., microservices to serve personalized recommendations) components. The team is responsible for mainly batch and streaming components as well as the underlying algorithms and evaluation methodologies.
In this role, you will design, build, and integrate scalable systems, platforms, and tools to provide better recommendations and personalization data with low latency. You will work in a wide stack including big data and streaming technologies as a part of a cross-functional agile team of engineers, data scientists, and product managers.
We are passionate about learning, making an impact, and building with quality. We love taking on new technical challenges. We are interested in building a diverse, collaborative, and fun environment. Come help us improve lives through learning!
Here’s what you’ll be doing:
- Design, develop, test, deploy, and maintain recommendation and personalization related systems, platforms, and tools at scale.
- Partner with data scientists to troubleshoot and optimize complex ML applications.
- Contribute to re-architecting Udemy’s next-generation recommendations and personalization systems.
- Collaborate with data scientists, engineers, and product managers to identify opportunities to improve our platform.
We’re excited about you because you have:
- 3+ years of full-time experience with software engineering or data engineering or equivalent
- Strong knowledge of algorithms and data structures
- Proficiency with Scala and Python
- Experience with big data storage and processing frameworks such as Hadoop, Hive, and Spark
- Experience with Kafka and Spark Streaming
- Experience in design, development, and maintenance of large-scale systems
- Self-driven, highly motivated, and able to learn quickly
- Ability to communicate effectively with non-technical stakeholders
Great if you have but not required:
- Experience in design and implementation of MLOps systems
- Experience in performance optimization of deep learning systems