Machine Learning Engineer 2
Core
Build and scale pipelines to turn raw conversation data into structured, searchable customer memory and evaluation systems for Twilio's Conversational AI platform.
Role type
Senior Machine Learning Engineer (Customer Memory)
Builds
Customer memory layer, extraction pipelines, retrieval systems, and evaluation benchmarks for Conversational AI
Domain
Telecommunications / Conversational AI / Large Language Models
Deliverable
production ML models
Required skills
Backend service development, LLM prompt engineering, vector search and embeddings, observability (logging/metrics/traces), evaluation system design, distributed system debugging
Preferred skills
Go, Python, event-streaming systems (Kafka), LLM-backed product experience, practical ML productionization
Technologies
LLMs, vector search, Kafka, embeddings
Responsibilities
Build extraction pipelines tuning LLM prompts and schemas; own retrieval path using embeddings and vector search; contribute to evaluation systems and regression gates; diagnose production issues across ingestion/extraction/indexing; partner with Product and ML teams on system changes
Seniority
Senior, hands-on IC
