Engineering Manager; ML Platform

Requirements

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

• 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
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• Your team will own platforms for training and deploying models and scaling systems that must operate reliably at Klaviyo’s data and traffic scale
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• This is a backend-heavy, hands-on technical leadership role
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• 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
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• This role is hybrid and based in Boston
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• Enable AI / ML teams across Klaviyo to ship new models and ML-powered features faster, more safely, and more reliably
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• Evolve our ML and LLM platform architecture so teams can build, evaluate, and operate production ML systems with consistent patterns and best practices
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• 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
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• Raise the bar on engineering and operational excellence for systems that support 167K+ customers and billions of events
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• Build and grow a high-performing, inclusive engineering team that operates with ownership, curiosity, and strong customer focus
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• Lead, coach, and grow a team of software / ML platform engineers (typically 6–10+ direct reports)
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• Set clear goals, provide regular feedback, and support career development aligned with Klaviyo’s Engineering Career Architecture
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• Stay hands-on with the technology: participate in design reviews, code reviews, and occasionally ship code for critical paths or prototypes
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• 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