✨ About The Role
- The role involves architecting and developing distributed systems for processing terabytes of image and video data.
- Responsibilities include managing containerized applications on Kubernetes and deploying distributed systems using Ray.
- The engineer will integrate machine learning models into data processing workflows, utilizing PyTorch for model serving.
- The position requires developing workflows that support high-throughput ingest and processing of media data across multiple cloud storage solutions.
- System optimization and monitoring are key aspects of the job, ensuring performance and reliability in distributed compute environments.
⚡ Requirements
- The ideal candidate will have over 5 years of experience in software development and data engineering, particularly in production distributed systems.
- A strong proficiency in Python is essential, with a focus on asynchronous programming and modular design.
- Experience managing and scaling containerized applications on Kubernetes is crucial for success in this role.
- Familiarity with distributed computing engines like Ray and machine learning frameworks such as PyTorch is highly desirable.
- The candidate should have a background in processing large image and video datasets, demonstrating efficient data handling and feature extraction skills.