Senior ML Platform Engineer - Scale Production AI (Equity)

Klaviyo; Boston (MA); On-site; USD 148,000 - 222,000; Full time

Job summary

Klaviyo in Boston is seeking a Senior Machine Learning Platform Engineer to build core platforms, tools, and infrastructure that ML/AI engineers rely on to power Klaviyo’s products. You will drive initiatives for training and deploying models, standardize feature data, and scale systems to support high data and traffic volumes.

This backend-heavy, individual contributor role requires mentoring, code reviews, and close collaboration with product, ML, data science, and infra partners to deliver

Qualifications

• 7+ years of experience building backend or distributed systems.
• Experience designing and launching AI/ML systems in production at scale.
• Strong Python proficiency or equivalent backend language.
• Experience with cloud infrastructure and platform fundamentals (AWS, Kubernetes).
• Familiarity with data-intensive systems (streaming/batch processing).
• Collaborating with cross-functional technical partners (ML, product, infra, security).
• Strong communication and engineering leadership across teams.

Responsibilities

• Design seamless workflows for continuous model training, inference, and monitoring.
• Lead technical execution, code/design reviews, and implement high-impact paths.
• Mentor engineers, promote engineering best practices and design standards.
• Drive architectural design and direction for ML Platform components.
• Define the ML Platform roadmap with product and engineering leaders.

Skills

Python

Backend development

Distributed systems

Cloud (AWS/Kubernetes)

ML/AI platform

Cross-functional collaboration

Communication skills

Job description

Klaviyo in Boston is seeking a Senior Machine Learning Platform Engineer to build core platforms, tools, and infrastructure that ML/AI engineers rely on to power Klaviyo’s products. You will drive initiatives for training and deploying models, standardize feature data, and scale systems to support high data and traffic volumes.

This backend-heavy, individual contributor role requires mentoring, code reviews, and close collaboration with product, ML, data science, and infra partners to deliver