Backend Engineer - ML-Powered Recommendations

Klaviyo Inc.; Boston (MA); Hybrid; USD 116,000 - 174,000; Full time

Job summary

Klaviyo is hiring a Software Engineer II for the Recommendations Platform Team in Boston, onsite 5 days a week. You will help architect backend services powering product recommendations across channels and build large-scale data pipelines leveraging Spark and vector databases.

You will collaborate with ML engineers and product stakeholders to productionize models, ensure observability, and drive data-driven decisions through experiments and A/B tests.

Qualifications

• 2+ years of professional software engineering experience with a focus on backend and distributed systems at scale.
• Proficient in Python.
• Comfortable with cloud-native architectures (AWS preferred) and container orchestration (Kubernetes).
• Experience in data-driven decision making and A/B testing.
• Comfortable designing and querying data models in relational, analytical, and NoSQL datastores.
• Familiar with modern DevOps practices (CI/CD, monitoring, alerting).
• Track record of owning features end-to-end.

Responsibilities

• Contribute to the architecture and evolution of backend services that power product recommendations across Klaviyo experiences.
• Contribute to and maintain robust, large-scale data processing pipelines (e.g., Apache Spark) delivering high-quality features.
• Collaborate with ML engineers and product stakeholders to productionize recommendation models.
• Develop the vector database powering recommendations and related use cases.
• Ensure data and service observability with metrics, logs and dashboards.
• Break down projects into milestones and balance experimentation with maintainability.
• Lead data-driven decision making and A/B testing efforts.

Skills

Python

Backend systems

Distributed systems

Spark

AWS

Kubernetes

Data pipelines

ML integration

A/B testing

Tools

Postgres

MySQL

Redis

Vector databases

Job description

Klaviyo is hiring a Software Engineer II for the Recommendations Platform Team in Boston, onsite 5 days a week. You will help architect backend services powering product recommendations across channels and build large-scale data pipelines leveraging Spark and vector databases.

You will collaborate with ML engineers and product stakeholders to productionize models, ensure observability, and drive data-driven decisions through experiments and A/B tests.