Engineering Manager, ML Platform

At Klaviyo, we believe the future of software lies not in productivity tools for human users but in software that can run and optimize itself based on outcome or reward metrics. We’ve built the infrastructure and application that serve as the interface between businesses and consumers. We now have over 167,000 customers, billions of consumer profiles, and hundreds of billions of customer messages and follow-on conversion data. We are building state-of-the-art AI and machine learning technologies at Klaviyo to power marketing agent, service agent, and personalization products such as smart send time, audience optimization and product recommendations.

As a Machine Learning Platform Engineering Manager, you will lead a team of engineers building the core platforms, tools, and infrastructure that ML and AI engineers rely on to create advanced agents and models powering Klaviyo’s products. Your team will own platforms for training and deploying models and scaling systems that must operate reliably at Klaviyo’s data and traffic scale.

This is a backend-heavy, hands-on technical leadership role. You will manage and grow engineers, shape the technical roadmap for ML Platform, and collaborate closely with product, ML, data science, and infrastructure partners to deliver durable, high-leverage platforms that accelerate AI development across Klaviyo.

This role is hybrid and based in Boston.

• Enable AI / ML teams across Klaviyo to ship new models and ML-powered features faster, more safely, and more reliably.
• Evolve our ML and LLM platform architecture so teams can build, evaluate, and operate production ML systems with consistent patterns and best practices.
• Improve reliability, observability, and cost efficiency of ML training, inference, and other ML workloads that serve features like smart send time, audience optimization and product recommendations.
• Raise the bar on engineering and operational excellence for systems that support 167K+ customers and billions of events.
• Build and grow a high-performing, inclusive engineering team that operates with ownership, curiosity, and strong customer focus.

• →Lead, coach, and grow a team of software / ML platform engineers (typically 6–10+ direct reports).
• →Set clear goals, provide regular feedback, and support career development aligned with Klaviyo’s Engineering Career Architecture.
• →Stay hands-on with the technology: participate in design reviews, code reviews, and occasionally ship code for critical paths or prototypes.
• →Partner with product and technical leaders to define and evolve the ML Platform strategy and roadmap, balancing short-term delivery with long-term platform investments.

Learn more about the team’s work in our blogs on Ray Jobs & Ray Tune.

We encourage candidates to apply even if they do not meet all the qualifications listed. ML Platform and MLOps are rapidly evolving spaces and we are all constantly learning.

• 7+ years of experience as a software engineer, ML platform engineer, or similar, building backend or distributed systems.
• 2+ years of experience in a formal people leadership role
• Demonstrated experience launching and operating AI/ML systems in production at scale
• Strong proficiency in Python (or a similar backend language such as Go, Java, or Scala).
• Experience with cloud infrastructure and platform fundamentals (AWS, kubernetes):
• Familiarity with data-intensive systems: streaming or batch processing, data modeling, and designing systems with large-scale data in mind (spark, ray-data).
• Comfortable collaborating with cross-functional technical partners (ML, product, infra, security).
• Strong communication skills and a track record of driving clarity and alignment across teams.