3 hours ago
Boston, MA, USAMid Level
H1B Sponsor
Base Salary
$116k - $174k/yr
Responsibilities
- Contribute to the architecture and evolution of reliable, performant backend services and clear APIs for product recommendations.
- Build and maintain large-scale data processing pipelines that transform events and catalog data into features and model inputs.
- Partner with ML engineers and product stakeholders to productionize recommendation models for batch and real-time inference.
- Contribute to the vector database supporting recommendations, semantic search, and agentic use cases.
- Implement observability through metrics, logging, tracing, and dashboards.
- Break projects into milestones while balancing experimentation, technical soundness, and maintainability.
- Lead data-driven decision-making and A/B testing, interpreting results to guide product and engineering iterations.
- Participate in on-call and incident response and drive post-incident improvements to system resilience and operability.
- Use AI to accelerate development, automate testing, and improve monitoring and debugging workflows.
- Share knowledge, mentor junior engineers, and define best practices for data frameworks, distributed systems, and production ML integration.
Requirements
- At least 2 years of professional software engineering experience focused on backend and distributed systems at scale.
- Proficiency in Python and willingness to work in other languages.
- Experience with cloud-native architectures, preferably AWS, and container orchestration such as Kubernetes.
- Experience with data-driven decision-making and A/B testing, including instrumenting experiments and interpreting results.
- Ability to design and query relational, analytical, and NoSQL data models, including systems such as Postgres, MySQL, data warehouses, Redis, and vector databases.
- Familiarity with DevOps practices including CI/CD, monitoring, and alerting for large-scale data and recommendation systems.
- Track record of owning features end to end, from technical design and implementation through rollout, monitoring, and iteration.
- Strong technical collaboration and communication skills across ML engineering, software engineering, product, and other teams.
- Experience experimenting with AI in professional or personal projects and interest in responsible AI tools and workflows.
- Preferred experience with recommendation systems or adjacent ML-powered features such as ranking, personalization, or search.
- Preferred experience with Apache Spark or comparable big-data frameworks such as Flink or Beam.
- Preferred experience integrating ML models into production systems or contributing to ML infrastructure.
- Preferred experience training and iterating on ranking, prediction, or personalization models.
- Preferred experience with ML and distributed-compute frameworks such as Ray.
- Preferred experience partnering with data science or ML teams on feature stores, offline/online parity, model deployment, and monitoring.
- Background in e-commerce, marketing technology, or consumer personalization is a plus.
Benefits
- Onsite in Boston, Massachusetts, five days per week.
- Base salary range of $116,000-$174,000 USD per year.
- Role may require up to 10% travel for onboarding, client or partner work, team meetings, and industry events.
- Comprehensive health, welfare, and wellbeing benefits are available based on eligibility.
- Potential additional compensation may include an annual cash bonus, equity, and sign-on payments.
Tech Stack
Categories
About Klaviyo
Klaviyo (NYSE: KVYO) is the autonomous B2C CRM. Powered by its built-in data platform and AI, Klaviyo combines marketing automation, analytics, and customer service into one unified solution, making it easy for businesses to know their customers and grow faster. Klaviyo (CLAY-vee-oh) helps over 193,000 brands like Mattel, Glossier, Daily Harvest, and Liquid Death deliver 1:1 experiences at scale, improve efficiency, and drive revenue.