Reddit is seeking a Principal Software Engineer to oversee the vision and strategic direction of Reddit’s ML Feature Platform, leading the development of scalable, real-time infrastructure that powers key features such as feeds ranking, content understanding, recommendations, and advertising. The goal is to architect and implement a cutting-edge feature store optimized for low-latency online inference at scale, supporting Reddit’s commitment to delivering personalized and engaging user experiences.
Requirements
- Deep expertise in systems design, performance optimization, and cloud-native architectures (AWS, GCP, Azure)
- Strong understanding of ML infrastructure, including feature engineering, data freshness, feature versioning, and online/offline feature retrieval
- Proven experience building real-time data systems such as feature stores, stream processing engines, or caching systems
- 10+ years of professional software engineering experience
- 3+ years of experience leading teams in designing large-scale distributed systems
Responsibilities
- Lead the technical strategy, architecture, and development of Reddit’s next-generation real-time ML feature store supporting online and offline feature retrieval
- Design and implement scalable infrastructure for feature computation, storage, and retrieval to support various platform components
- Collaborate with ML, data engineering, and infrastructure teams to enhance the ML platform capabilities and performance
- Mentor team members on best practices in DevOps, system reliability, and infrastructure health management
- Drive innovation by exploring new technologies and methodologies to improve ML feature management at scale
- Oversee the vision and strategic direction of Reddit’s ML Feature Platform
- architecting and implementing a cutting-edge feature store optimized for low-latency online inference at scale
Other
- Excellent organizational and communication skills
- Experience working with cross-functional teams and managing project timelines and deliverables
- Work closely with management to set team goals, plan projects, and mitigate risks to ensure successful delivery
- Collaboration with cross-functional teams, mentoring engineers, and ensuring robust, high-performance ML infrastructure are core aspects of this position.
