Senior Machine Learning Engineer (Nova)

Iterable is the leading AI-powered customer engagement platform that helps leading brands create dynamic, individualized experiences at scale. The Senior Machine Learning Engineer will build core Machine Learning foundations to power agentic experiences, focusing on applied Machine Learning in production environments and collaborating with cross-functional teams.

Responsibilities:

• 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
• 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

Requirements:

• 5+ years experience as a Machine Learning Engineer or similar role focused on production systems
• Strong engineering skills with Python or TypeScript, including experience building ML workflows in frameworks like Mastra or comparable agent/LLM toolkits
• Experience with retrieval systems, vector databases, search technologies, or RAG architectures
• Prior work integrating ML or LLM-powered features into production applications
• Understanding of ML evaluation techniques, experimentation design, and failure analysis
• Ability to lead complex projects, make practical trade-offs, and work independently in areas of ambiguity
• Strong communication and collaboration skills in a distributed environment
• Experience building ML or LLM platforms, tooling, or developer-facing frameworks
• Prior work with embeddings, search–ranking systems, or advanced RAG architectures
• Familiarity with event-driven systems or streaming architectures
• Experience with model observability, performance monitoring, or proactive regression detection
• Background in personalization, recommendations, or applied NLP
• Experience working in remote-first engineering teams