Senior Machine Learning Platform Engineer
About The Position
Klaviyo is hiring a Senior Machine Learning Platform Engineer to build the core platforms, tools, and infrastructure that AI and machine learning engineers use to develop advanced agents and models for Klaviyo products. The role will help evolve ML and LLM platform architecture, support model training and deployment, standardize feature data, and scale reliable systems for Klaviyo’s data and traffic volumes. The platform supports products including Composer, smart send time, audience optimization, and product recommendations. This is a backend-heavy, hands-on technical individual contributor position based in Boston. The engineer will lead technical execution, write high-impact code for critical paths, conduct code and design reviews, and collaborate with product, machine learning, data science, infrastructure, and security partners. The role also includes mentoring engineers, shaping technical direction and roadmap, and improving the reliability, observability, and cost efficiency of ML workloads. The position may require up to 10% travel, coordinated in advance.
Requirements
- At least 7 years of experience as a software engineer, ML platform engineer, or in a similar role 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, including AWS and Kubernetes.
- Familiarity with data-intensive systems, including streaming or batch processing, data modeling, and designing for large-scale data; examples listed include Spark and Ray Data.
- Ability to collaborate with cross-functional technical partners in ML, product, infrastructure, and security.
- Strong communication skills and a track record of driving technical excellence across teams.
Responsibilities
- Enable AI and ML teams across Klaviyo to ship models and ML-powered features faster, more safely, and more reliably.
- Evolve ML and LLM platform architecture so teams can build, evaluate, and operate production ML systems using consistent patterns and best practices.
- Improve reliability, observability, and cost efficiency of ML training, inference, and other ML workloads.
- Architect and scale systems for feature storage and real-time retrieval for training and inference datasets.
- Design workflows with AI and ML application teams for continuous model training, inference, and monitoring.
- Lead technical execution, conduct code and design reviews, and author high-impact code for critical system paths.
- Mentor engineers across the organization and promote engineering excellence, best practices, and strong design standards.
- Drive architectural design and technical direction for core ML and Feature platform components.
- Partner with product and engineering leaders to define the ML Platform roadmap.
- Own delivery, reliability, and operational health of key ML Platform systems in the engineer’s area.
- Participate in on-call and incident management for the team’s services.
- Contribute to broader AI/ML strategy and platform direction.
Benefits
- The total compensation package may include participation in the company’s annual cash bonus plan, equity, and sign-on payments.
- Comprehensive health, welfare, and wellbeing benefits based on eligibility.
- Accommodations are provided as needed.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
