Iterable is looking to build the core Machine Learning foundations that power Nova’s agentic experiences, focusing on applied Machine Learning in production environments, including retrieval systems, evaluation frameworks, and model integration layers.
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.
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.
Other
- Bachelor's, Master's, or Ph.D. degree in a relevant field (not explicitly mentioned but implied)
- 5+ years of experience in a relevant field
- Ability to work in a fast-moving, cross-functional product environment
- Strong communication and collaboration skills
- Ability to lead complex projects and make practical trade-offs
