Position Overview
We are looking for a Senior Machine Learning Engineer to build the core Machine Learning foundations that power Nova’s agentic experiences. This role focuses on applied Machine Learning in production environments: retrieval systems, evaluation frameworks, and model integration layers that make AI features reliable, scalable, and repeatable. You will design and implement the underlying components that support rich, intelligent interactions in the Iterable platform.
You will work closely with backend, frontend, and product teams to shape how Machine Learning is introduced and maintained across the company. The work blends hands-on engineering with system design, and is ideal for someone who can drive complex efforts independently, make practical architectural decisions, and collaborate in a fast-moving, cross-functional product 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.
- 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.
Qualifications
- 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.
Bonus Points
- 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.