Machine Learning Engineer

Twilio Twilio · Enterprise · Ireland · Remote · Engineering

Machine Learning Engineer to design and engineer AI-powered features for customer conversations, extracting meaning from voice and messaging data at scale. Responsibilities include implementing end-to-end ML pipelines, deploying production inference services, and monitoring performance. Requires 2+ years of ML engineering experience, Python, an ML framework, and experience with LLMs.

What you'd actually do

  1. Design and development of machine learning solutions, ensuring accuracy, performance, security, and scalability.
  2. Implement and maintain end-to-end AI/ML pipelines - from data ingestion and feature engineering through to model development, validation, and deployment with guidance from senior engineers on complex architectural decisions
  3. Instrument AI/ML services with appropriate metrics, logging, and telemetry to monitor model performance and operational health against defined SLOs
  4. Participate in on-call rotations, executing progressive rollouts and applying standard mitigation strategies to keep production inference services healthy
  5. Collaborate across planning, design, and code review phases contributing to product and technical discussions, while helping raise overall code quality through thoughtful review feedback

Skills

Required

  • Python
  • PyTorch
  • TensorFlow
  • JAX
  • Hugging Face Transformers
  • NLTK
  • SpaCy
  • AWS
  • GCP
  • Azure
  • Large Language Models

Nice to have

  • conversational AI
  • LLM fine-tuning
  • prompt engineering
  • LangGraph
  • AutoGen
  • CrewAI
  • MLOps
  • LLMOps

What the JD emphasized

  • production inference
  • production context

Other signals

  • design and engineer AI powered features
  • extract meaning from voice and messaging data
  • develop and deploy solutions
  • model pipelines to production inference
  • customer conversations smarter