Senior Machine Learning Engineer (Nova)

Join Iterable as a Senior Machine Learning Engineer, where you will build the core Machine Learning foundations that power Nova's agentic experiences. This role focuses on applied Machine Learning in production environments, including retrieval systems, evaluation frameworks, and model integration layers. You will collaborate with backend, frontend, and product teams to shape how Machine Learning is introduced and maintained across the company.

• Design and implement the underlying components that support rich, intelligent interactions in the Iterable platform, 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, and develop generalized evaluation frameworks for LLM- and agent-based features.
• Collaborate with product, design, and engineering teams to align ML system design with user experience and product goals, and ensure secure, robust handling of data used in ML workflows.
• Strong communication and collaboration skills in a distributed environment
• Ability to lead complex projects, make practical trade-offs, and work independently in areas of ambiguity
• Understanding of ML evaluation techniques, experimentation design, and failure analysis
• 5+ years experience as a Machine Learning Engineer or similar role focused on production systems
• Experience with retrieval systems, vector databases, search technologies, or RAG architectures
• Strong engineering skills with Python or TypeScript, including experience building ML workflows in frameworks like Mastra or comparable agent/LLM toolkits
• Prior work integrating ML or LLM-powered features into production applications
• Experience building ML or LLM platforms, tooling, or developer-facing frameworks
• Prior work with embeddings, search–ranking systems, or advanced RAG architectures
• Experience with model observability, performance monitoring, or proactive regression detection
• Familiarity with event-driven systems or streaming architectures
• Background in personalization, recommendations, or applied NLP
• Experience working in remote-first engineering teams