Software Engineer- Product Recommendations

<div class="content-intro"><p><em>At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit <a class="_ymio1r31 _ypr0glyw _zcxs1o36 _mizu194a _1ah3dkaa _ra3xnqa1 _128mdkaa _1cvmnqa1 _4davt94y _4bfu18uv _1hms8stv _ajmmnqa1 _vchhusvi _kqswh2mm _ect4ttxp _syaz13af _1a3b18uv _4fpr8stv _5goinqa1 _f8pj13af _9oik18uv _1bnxglyw _jf4cnqa1 _30l313af _1nrm18uv _c2waglyw _1iohnqa1 _9h8h12zz _10531ra0 _1ien1ra0 _n0fx1ra0 _1vhv17z1" href="http://klaviyo.com/careers" data-renderer-mark="true">klaviyo.com/careers</a> to see how we empower creators to own their own destiny.</em></p></div><p><strong>As the Software Engineer, Product Recommendations at Klaviyo, you’ll help build the machine learning–powered systems that decide which products to show to whom and when across our platform. You’ll work on large-scale backend and data systems that turn billions of behavioral events into real-time, personalized product recommendations that drive revenue for merchants of all sizes.</strong></p> <p><strong>You’ll join the Product Recommendation team, partnering closely with Machine Learning Engineers, AI Engineers, other engineers, Product Managers and Designers to design, build, and operate services and data pipelines that power our recommendation features end to end—from data ingestion and feature generation to ranking models and APIs exposed in product. This is a hands-on backend role with a strong focus on building scalable systems and data processing frameworks, with prior ML system experience as a plus (not a hard requirement).</strong></p> <h3><strong>How you’ll make a difference</strong></h3> <p><strong>Design, build, and operate backend services that power product recommendations across Klaviyo experiences (email, SMS, KAgent, onsite, etc.), with a focus on reliability, performance, and clear APIs.<br><br>Build and maintain large-scale data processing pipelines (e.g., using Apache Spark or similar frameworks) that transform raw events and catalog data into high-quality features and inputs for recommendation models.<br><br>Collaborate with ML engineers to productionize recommendation models—defining interfaces, feature contracts, and deployment patterns for batch and/or real-time inference. <br>Build ML/AI systems such as vector search that power recommendation, semantic search, and agentic use cases.<br><br>Implement and evolve data and service observability (metrics, logging, tracing, dashboards) to ensure recommendations are correct, fast, and available when customers need them.<br><br>Contribute to and improve shared data frameworks, libraries, and patterns that make it easier to build new recommendation use cases and iterate quickly.<br><br>Work with product managers to break down complex recommendation initiatives into clear milestones, helping balance experimentation speed with reliability and technical soundness.<br><br>Partner on data-driven decision making and A/B testing—ensuring recommendation systems are instrumented with the right metrics, and helping interpret results to guide future iterations.<br><br>Participate in on-call and incident response for the systems you own, driving follow-ups that improve the resilience and operability of our recommendation stack.<br><br>Transform workflows by putting AI at the center, building smarter systems and ways of working from the ground up—for example, using AI to accelerate development, automate tests, or better monitor and debug recommendation behavior.<br><br>Share knowledge and mentor other engineers on working with large-scale data frameworks, distributed systems, and best practices for integrating ML ... (truncated, view full listing at source)