Software Engineer II - Recommendations | Klaviyo Careers

Join the Recommendations Platform Team, which builds and deploys machine learning-based recommendation systems at scale. The team acts as a layer of product intelligence, personalizing messages with the right item at the right time across email, SMS, KAgent, onsite, and more. Its systems span large-scale data pipelines, batch training and inference, and low-latency online retrieval and ranking.

Key Responsibilities

• Contribute to the architecture and evolution of backend services that power product recommendations across Klaviyo experiences
• Build and maintain large-scale data pipelines (e.g., Apache Spark) that turn raw events and catalog data into high-quality model inputs, ensuring data quality and lineage
• Collaborate with ML engineers and product stakeholders to productionize recommendation models for batch and real-time inference
• Contribute to the vector database that powers recommendations, semantic search, and agentic use cases
• Ensure observability through metrics, logging, tracing, and dashboards
• Work with Product to break projects into clear milestones, balancing rapid experimentation with long-term maintainability
• Lead data-driven decision making and A/B testing, and interpret results to guide future iterations
• Participate in on-call and incident response, driving post-incident improvements
• Integrate AI into development workflows, such as accelerating development, automating tests, and building smarter monitoring tools
• Mentor junior engineers and define best practices for large-scale data frameworks, distributed systems, and production ML

Requirements

• 2+ years of professional software engineering experience in backend and distributed systems at scale
• Proven track record with production services, optimizing for latency, reliability, and operability
• Proficiency in Python and openness to other languages
• Comfort with cloud-native architectures (AWS preferred) and container orchestration such as Kubernetes
• Experience managing infrastructure and CI/CD pipelines
• Experience with data-driven decision making and A/B testing
• Experience designing and querying data models in relational, analytical, and NoSQL datastores (e.g., Postgres, MySQL, data warehouses, Redis, vector databases)
• Familiarity with modern DevOps practices (CI/CD, monitoring, alerting)
• Track record of owning features end to end, from design through rollout and iteration
• Hands-on experimentation with AI in work or personal projects

Skills

Technical Skills

• Python
• AWS, Kubernetes, CI/CD
• Apache Spark or similar data frameworks
• Postgres, MySQL, Redis, data warehouses, vector databases
• A/B testing and experimentation
• Observability (metrics, logging, tracing)

Soft Skills

• Clear communication of technical trade-offs to technical and non-technical partners
• Cross-team collaboration with ML engineers, software engineers, and PMs
• Self-starter mindset and ownership
• Mentoring

Nice to Have

• Experience with product recommendation systems or related ML features (ranking, personalization, search)
• Experience with Spark, Flink, Beam, or similar frameworks for batch or streaming pipelines
• Experience with AI/ML systems and integrating models into production
• Experience training and iterating on ML models
• Experience with Ray or similar distributed compute frameworks
• Experience partnering with data science teams on feature stores, offline/online parity, and model monitoring
• Background in e-commerce, marketing tech, or consumer personalization

Job Details

• Location: Boston, MA (up to 10% travel for onboarding, team meetings, and events)
• Work Mode: Onsite, 5 days a week
• Salary: $116,000 - $174,000 USD base (varies by skills, experience, and location)

Benefits

• Annual cash bonus plan, equity, and sign-on payments (based on eligibility)
• Comprehensive health, welfare, and wellbeing benefits