Remote ML Engineer - Conversational AI & Production

Twilio; Spain (TX); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Twilio in Spain is seeking a Machine Learning Engineer to design and deploy AI-powered features for smarter customer conversations at scale. You will work on the Conversation Intelligence team, building pipelines from data ingestion to production inference, collaborating with experienced ML engineers.

The role emphasizes experimentation, model validation, and measurable impact, using Python, PyTorch/TensorFlow, and NLP tools, with remote-first policy and occasional in-person meetings.

Qualifications

• Degree or equivalent in a quantitative field with strong analytical skills.
• 2+ years in ML engineering with Python and ML frameworks.
• Experience deploying ML services and using cloud infrastructure.
• Proficiency in Python and familiarity with NLP libraries.
• Experience with LLMs and production-grade AI/ML pipelines.
• Strong written and verbal communication; able to explain complex ideas.

Responsibilities

• Design and develop ML solutions with emphasis on accuracy, performance, security and scalability.
• Build and maintain end-to-end AI/ML pipelines from data to deployment.
• Instrument services with metrics, logging and telemetry to monitor health against SLOs.
• Participate in on-call rotations and manage production inference reliability.
• Collaborate across planning, design and code reviews to improve code quality.

Skills

Python

Machine Learning

NLP libraries

Model deployment

Cloud infrastructure

Communication skills

LLMs

Education

Bachelor's degree in Computer Science/Math/Statistics or equivalent

Tools

PyTorch

TensorFlow

JAX

Hugging Face Transformers

NLTK

SpaCy

AWS

GCP

Azure

Job description

Twilio in Spain is seeking a Machine Learning Engineer to design and deploy AI-powered features for smarter customer conversations at scale. You will work on the Conversation Intelligence team, building pipelines from data ingestion to production inference, collaborating with experienced ML engineers.

The role emphasizes experimentation, model validation, and measurable impact, using Python, PyTorch/TensorFlow, and NLP tools, with remote-first policy and occasional in-person meetings.