Machine Learning Engineer

Twilio Twilio · Enterprise · Spain · Remote · Engineering

Machine Learning Engineer on the Conversation Intelligence team to design and engineer AI powered features that extract meaning from voice and messaging data at Twilio scale. Develop and deploy solutions from model pipelines to production inference.

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
  • MLOps
  • LLMOps
  • AWS
  • GCP
  • Azure

Nice to have

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

What the JD emphasized

  • 2+ years of experience in machine learning engineering or applied ML
  • Experience developing, testing, and deploying small-to-medium scoped ML services or features in a collaborative engineering environment
  • Utilizing Large (or Small) Language Models within software systems

Other signals

  • design and engineer AI powered features
  • extract meaning from voice and messaging data
  • develop and deploy solutions
  • ship real features - from model pipelines to production inference