Senior Machine Learning Engineer (Nova)

Iterable is the leading AI-powered customer engagement platform that helps leading brands create dynamic, individualized experiences at scale. They are seeking a Senior Machine Learning Engineer to build core Machine Learning foundations for Nova’s agentic experiences, focusing on applied Machine Learning in production environments.

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