Senior ML Engineer - Agentic Context Retrieval & Search

Iterable, Inc.; Austin (TX); On-site; USD 150,000 - 250,000; Full time

Job summary

Iterable, Inc. is the AI customer engagement platform used by thousands of enterprises. As a Senior Machine Learning Engineer on Nova, you will lead the retrieval and search stack to ground agent responses in evidence, handling structured and unstructured data with real-time context awareness.

You will own end-to-end research, experimentation, and production deployment, shaping the AI direction at Iterable and mentoring engineers on the team.

Qualifications

• 5+ years of hands-on MLE experience putting complex models into production at scale, including search, information retrieval, or recommendation systems.
• Master's or PhD in Computer Science, Machine Learning, AI, or a related field.
• Experience with production search engines and relevance tuning.
• Experience with RAG, query rewriting, reranking, and grounding to reduce hallucination.
• Experience building agents on top of retrieval with multi-hop search.
• Strong evaluation practice: offline benchmarks, A/B testing, and labeling pipelines.

Responsibilities

• Build retrieval across structured and unstructured data.
• Develop semantic query understanding for agents (rewriting, classification, entity resolution).
• Create pipelines to extract entities, embeddings, summaries, and metadata.
• Build search subagents for retrieval decisions and multi-hop searches.
• Measure quality with ranking metrics and online tests; improve retrieval and harness.
• Mentor engineers and help set Nova's technical direction.

Skills

MLE in production

Information retrieval

Search systems

Recommender systems

Query understanding

Multi-hop search

Evaluation & A/B testing

Education

Master's degree in CS/ML/AI

Tools

Elasticsearch

OpenSearch

Vespa

RAG tooling

Job description

Iterable, Inc. is the AI customer engagement platform used by thousands of enterprises. As a Senior Machine Learning Engineer on Nova, you will lead the retrieval and search stack to ground agent responses in evidence, handling structured and unstructured data with real-time context awareness.

You will own end-to-end research, experimentation, and production deployment, shaping the AI direction at Iterable and mentoring engineers on the team.