Overview
Twilio is hiring a Machine Learning Engineer to design and engineer AI-powered features for Conversation Intelligence at scale.
What you'll do
- Design and develop machine learning solutions focused on accuracy, performance, security, and scalability.
- Build and maintain end-to-end AI/ML pipelines from data ingestion and feature engineering through deployment.
- Instrument AI/ML services with metrics, logging, and telemetry to monitor model performance and operational health.
- Participate in on-call rotations and execute progressive rollouts with mitigation strategies for inference services.
- Collaborate across planning, design, and code review to support product and technical discussions and improve code quality.
What you'll need
- Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related quantitative field, or equivalent practical experience.
- 2+ years of experience in machine learning engineering or applied ML.
- Demonstrated proficiency in Python and at least one ML framework: PyTorch, TensorFlow, or JAX.
- Familiarity with NLP libraries such as Hugging Face Transformers, NLTK, or SpaCy.
- Experience developing, testing, and deploying small-to-medium scoped ML services/features, including model versioning and experiment tracking.
- Experience with cloud infrastructure including AWS, GCP, or Azure.
- Experience utilizing Large (or Small) Language Models within software systems.
- Excellent written and verbal communication skills for technical and non-technical audiences.
Nice to have
- Hands-on experience with conversational AI, or LLM fine-tuning and prompt engineering in a production context.
- Exposure to agentic AI frameworks such as LangGraph, AutoGen, or CrewAI.
- Familiarity with MLOps/LLMOps tooling for maintaining models in production (testing, versioning, model registry, retraining, monitoring).
Details
- Remote from Ireland.
- Occasional travel may be required for in-person team or project meetings.
Read the full description and apply on the company’s own careers page.
