The opportunity
Iterable is the leading AI-powered customer engagement platform that helps leading brands like Redfin, SeatGeek, Priceline, Calm, and Box create dynamic, individualized experiences at scale. Our platform empowers organizations to activate customer data, design seamless…
What you'll do
Design and build Machine Learning platform components that support agentic: systems, including retrieval pipelines, indexing strategies, and model integration layers.
Introduce and operationalize RAG use cases, from data sourcing and embedding: generation to runtime retrieval patterns.
Develop generalized evaluation frameworks for LLM: and agent-based features, including offline metrics, golden datasets, and continuous monitoring.
Implement abstractions, tooling, and reusable patterns that enable other: teams to build ML- and LLM-powered experiences efficiently.
Partner with backend engineers to productionize ML features with strong: reliability, observability, and performance characteristics.
Prototype applied ML solutions to validate feasibility before investing in full builds.
What they're looking for
- Ensure secure, robust handling of data used in ML workflows and retrieval operations.
- Collaborate with product, design, and engineering to align ML system design: with user experience and product goals.
- Contribute to iterative improvements of the Nova agent framework, including: workflows built with Mastra and TypeScript.
- + years of experience as a Machine Learning Engineer or similar role focused on production systems.
