Senior ML Platform Engineer | Klaviyo Jobs | Boston, MA

Klaviyo is building state-of-the-art AI and machine learning technologies to power Composer and personalization products such as smart send time, audience optimization, and product recommendations. As a Senior Machine Learning Platform Engineer, you will help build the core platforms, tools, and infrastructure that ML and AI engineers rely on to create advanced agents and models. You will drive technical initiatives for training and deploying models, unifying and standardizing feature data, and scaling systems that must run reliably at Klaviyo’s data and traffic scale. This is a backend-heavy, hands-on individual contributor role in which you lead technical execution, review code and designs, and write high-impact code for critical system paths.

Key Responsibilities

• Enable AI/ML teams across Klaviyo to ship new models and ML-powered features faster, more safely, and more reliably
• Evolve the ML and LLM platform architecture so teams can build, evaluate, and operate production ML systems with consistent patterns and best practices
• Improve the reliability, observability, and cost efficiency of ML training, inference, and other ML workloads behind 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
• Architect and scale systems for feature storage and real-time retrieval for training and inference datasets
• Work with AI and ML application teams to design seamless workflows for continuous model training, inference, and monitoring
• Lead technical execution, conduct code and design reviews, and write high-impact code for critical system paths
• Mentor engineers across the organization, promoting engineering excellence, best practices, and strong design standards
• Drive architectural design and technical direction for core components of the ML and Feature platforms
• Partner with product and engineering leaders to define the ML Platform roadmap

Requirements

• 7+ years of experience as a software engineer, ML platform engineer, or similar, building backend or distributed systems
• Demonstrated experience designing and launching 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 for large-scale data (e.g., Spark, Ray Data)
• Comfort collaborating with cross-functional technical partners (ML, product, infrastructure, security)
• Strong communication skills and a track record of driving technical excellence across teams
• Education: Not specified

Skills

Technical Skills

• Python (or Go, Java, Scala)
• AWS and Kubernetes
• Spark and Ray Data
• ML training and inference platforms
• Feature storage and real-time retrieval
• Observability and production operations

Soft Skills

• Technical leadership and mentoring
• Cross-functional collaboration
• Clear communication
• Driving engineering excellence across teams

Success Measures

• 30 days: Complete Klaviyo boot camp and onboarding for the AI & Analytics organization, build context on the AI/ML stack and roadmap, meet your team and key stakeholders, and onboard to existing workstreams and production ML deployment pipelines
• 60 days: Deliver high-impact architectural enhancements or core features across the ML Platform, conduct deep technical dives and mentor peers through reviews, help set technical standards for feature platform components, and help shape the next 2-3 quarters of roadmap
• 90 days: Own delivery, reliability, and operational health of key ML Platform systems in your area, have multiple features or capabilities in active use by ML/AI product teams, take part in on-call and incident management, and contribute to broader AI/ML strategy

Benefits

• Total compensation may include an annual cash bonus, equity, and sign-on payments, depending on eligibility
• Comprehensive health, welfare, and wellbeing benefits