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Klaviyo is seeking a Software Engineer II to join the Recommendations Platform Team, responsible for building and scaling machine learning-based recommendation systems. This role focuses on developing backend services that power product recommendations across Klaviyo's platform (email, SMS, KAgent, onsite), including large-scale data processing pipelines, vector databases, and real-time inference systems.
Key responsibilities include architecting and evolving backend services for recommendations with emphasis on reliability, performance, and clear APIs; building and maintaining robust data processing pipelines using frameworks like Apache Spark to transform raw events and catalog data into high-quality features; collaborating with ML engineers and product teams to productionize recommendation models; developing vector database infrastructure for recommendations and semantic search; ensuring comprehensive observability through metrics, logging, tracing, and dashboards; breaking down projects into clear milestones balancing experimentation with technical soundness; leading data-driven decision-making and A/B testing efforts; participating in on-call and incident response; integrating AI into development workflows; and mentoring junior engineers on distributed systems and ML production patterns.
You bring 2+ years of professional software engineering experience focused on backend and distributed systems at scale, with proven track record optimizing for latency, reliability, and operability. You're proficient in Python, comfortable with cloud-native architectures (AWS preferred) and container orchestration (Kubernetes), experienced in data-driven decision-making and A/B testing, and comfortable designing and querying data models across relational, analytical, and NoSQL datastores. Experience with large-scale data frameworks, ML systems, and production infrastructure is valued. The role requires 5 days per week onsite in Boston.
