Klaviyo · 7 hours ago
Software Engineer- Product Recommendations
United States
Full-time
Remote
Mid Level
$120K/yr - $180K/yr
3+ years expKlaviyo is a company that empowers creators to own their destiny by making first-party data accessible and actionable. The Software Engineer for Product Recommendations will be responsible for building machine learning-powered systems that provide personalized product recommendations, collaborating with various teams to design and operate scalable backend services and data pipelines.
AdvertisingAnalyticsE-CommerceMarketing AutomationSoftware
Responsibilities
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
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
Collaborate with ML engineers to productionize recommendation models—defining interfaces, feature contracts, and deployment patterns for batch and/or real-time inference
Build ML/AI systems such as vector search that power recommendation, semantic search, and agentic use cases
Implement and evolve data and service observability (metrics, logging, tracing, dashboards) to ensure recommendations are correct, fast, and available when customers need them
Contribute to and improve shared data frameworks, libraries, and patterns that make it easier to build new recommendation use cases and iterate quickly
Work with product managers to break down complex recommendation initiatives into clear milestones, helping balance experimentation speed with reliability and technical soundness
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
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
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
Share knowledge and mentor other engineers on working with large-scale data frameworks, distributed systems, and best practices for integrating ML into production systems
Qualification
Required
3+ years of software engineering experience, including building and operating backend services in production
Strong focus on backend and distributed systems at scale; you've worked on high-throughput or highly available services and care about latency, reliability, and operability
Proficient in Python, and comfortable working in at least one modern language used for backend/data work (e.g., Java or Scala)
Proficient with big data frameworks such as Apache Spark (or similar technologies like Flink, Beam, etc.) for building batch or streaming pipelines
Comfortable with cloud-native architectures (AWS preferred) and container orchestration (e.g., Kubernetes); able to work with infrastructure and CI/CD pipelines as part of your day-to-day development
Comfortable with data-driven decision making and A/B testing—you understand how to instrument experiments, read results, and fold learnings back into the system
Comfortable designing and querying data models in relational or analytical datastores (e.g., Postgres, MySQL, data warehouses)
Familiarity with modern DevOps practices (CI/CD, monitoring, alerting) and how they apply to large-scale data and recommendation systems
Proven track record of owning projects end-to-end—from design and implementation through rollout, monitoring, and iteration—ideally across multiple components or services
Excellent collaborator and communicator: you can explain tradeoffs to technical and non-technical partners and work effectively with ML Engineers, Software Engineers, PMs, and other teams
You've already experimented with AI in work or personal projects, and you're excited to dive in and learn fast. You're hungry to responsibly explore new AI tools and workflows, finding ways to make your work smarter and more efficient
Preferred
Previous experience working on product recommendation systems or adjacent ML-powered features (ranking, personalization, search, or similar)
Experience in AI/ML systems and products, such as integrating models into production systems or building features powered by ML
Experience training machine learning models (e.g., for ranking, prediction, or personalization), even if you don't consider yourself a full-time ML engineer
Experience with ML and distributed compute frameworks such as Ray or similar tools
Experience partnering with data science or ML teams to productionize models (feature stores, offline/online parity, model deployment and monitoring)
Experience with additional data technologies (e.g., Kafka, Kinesis, Redis, feature stores, or vector databases)
Background in e-commerce, marketing tech, or consumer personalization products
Benefits
Participation in the company’s annual cash bonus plan
Variable compensation (OTE) for sales and customer success roles
Equity
Sign-on payments
A comprehensive range of health, welfare, and wellbeing benefits based on eligibility
Company
Klaviyo
Klaviyo is an automation and email platform designed to help grow businesses.
1001-5000 employees
H1B Sponsorship
Klaviyo has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (47)
2024 (29)
2023 (24)
2022 (27)
2021 (21)
2020 (8)
Funding
Current Stage
Public CompanyTotal Funding
$1.35BKey Investors
ShopifySands Capital VenturesAccel
2025-08-13Post Ipo Secondary· $195.06M
2025-05-14Post Ipo Secondary· $372.95M
2023-09-20IPO
Leadership Team
Andrew Bialecki
CEO
Ed Hallen
Co-Founder, Chief Strategy Officer, Board Member
Recent News
Investing.com
2026-01-03
2025-12-17
Company data provided by crunchbase