Reddit is looking to design and implement the next generation backend ML systems that power the personalized feeds on Reddit, aiming to balance speed, relevance, and reliability for millions of users.
Requirements
- 8+ years of experience as a software engineer developing backend ML systems at scale, using Go, Python, C++ or any object oriented programming language
- Experience with building large-scale distributed systems and data intensive applications
- Experience with developing and improving MLOps tools such as deployment, automation, system diagnosis, reproducibility, model monitoring etc.
- Experience designing and implementing performant, stable, and maintainable interfaces for Machine Learning systems
- Familiar with software engineering best practices such as unit testing and code reviews, design, and documentation
Responsibilities
- Design and implement the next generation backend ML systems that power the personalized feeds on Reddit
- Work closely with ML engineers to design and implement scalable interfaces
- Explore new technologies that help grow our ML systems capabilities
- Champion and drive engineering processes and best practices
- Write efficient, scalable and maintainable code that will help us iterate quickly and safely
- Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing.
- Drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making.
Other
- Strong organizational skills with the ability to prioritize tasks and keep projects on schedule with a strong attention to detail
- BS degree in Computer Science, a similar technical field of study or equivalent practical experience
- Entrepreneurial spirit. You are self-directed, innovative, and biased towards action in fast-paced environments. You love to build new things and thrive in ambiguity and even failure
- Excellent communication skills. You collaborate effectively with teams in a fully remote environment and discuss complex topics with technical and non-technical audiences
