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Salary: USD 148,000 - 222,000 / annual
Klaviyo is building state-of-the-art AI and machine learning technologies to power Composer and personalization products like smart send time, audience optimization, and product recommendations. The company serves over 167,000 customers and processes billions of consumer profiles and customer messages.
As a Senior Machine Learning Platform Engineer, you will be a backend-heavy, hands-on technical individual contributor responsible for building core platforms, tools, and infrastructure that ML and AI engineers rely on. You will drive key technical initiatives for training and deploying models, unifying and standardizing feature data, and scaling systems that operate reliably at Klaviyo's data and traffic scale.
Key responsibilities include:
- Enabling AI/ML teams across Klaviyo to ship new models and ML-powered features faster, more safely, and more reliably
- Evolving the ML and LLM platform architecture so teams can build, evaluate, and operate production ML systems with consistent patterns and best practices
- Improving reliability, observability, and cost efficiency of ML training, inference, and other ML workloads
- Raising the bar on engineering and operational excellence for systems supporting 167K+ customers and billions of events
- Architecting and scaling systems supporting feature storage and real-time retrieval for training and inference datasets
- Working closely with AI & ML application teams to design seamless workflows for continuous model training, inference, and monitoring
- Leading technical execution, conducting code and design reviews, and authoring high-impact code for critical system paths
- Mentoring engineers across the organization and promoting engineering excellence and best practices
- Driving architectural design and technical direction for core ML and Feature platform components
- Partnering with product and engineering leaders to define the ML Platform roadmap
In your first 90 days, you will complete onboarding, build context on the AI/ML stack and platform components, meet key stakeholders, deliver high-impact architectural enhancements, conduct technical dives and code reviews, partner with staff/principal engineers to establish technical standards, and own accountability for delivery and reliability of key ML Platform systems.
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 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 track record of driving technical excellence across teams
