Twilio: Machine Learning Engineer

Headquarters: Remote - Ireland

See yourself at Twilio

Join the team as Twilio’s next Machine Learning Engineer.

About the job

This position is to design and engineer AI powered features that makes every customer conversation smarter. As a Machine Learning Engineer on the Conversation Intelligence team, you'll develop and deploy solutions that extract meaning from voice and messaging data at Twilio scale. You'll work alongside experienced ML practitioners to ship real features - from model pipelines to production inference - that directly shape how businesses understand their customers.

Responsibilities

In this role, you’ll:

• Design and development of machine learning solutions, ensuring accuracy, performance, security, and scalability.
• 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
• Instrument AI/ML services with appropriate metrics, logging, and telemetry to monitor model performance and operational health against defined SLOs
• Participate in on-call rotations, executing progressive rollouts and applying standard mitigation strategies to keep production inference services healthy
• Collaborate across planning, design, and code review phases contributing to product and technical discussions, while helping raise overall code quality through thoughtful review feedback

Qualifications 

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

*Required:

• 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, with demonstrated proficiency in Python and at least one ML framework (PyTorch, TensorFlow, or JAX) and familiarity with NLP libraries such as Hugging Face Transformers, NLTK, or SpaCy.
• Experience developing, testing, and deploying small-to-medium scoped ML services or features in a collaborative engineering environment, including model versioning, experiment tracking, and cloud-based infrastructure (AWS, GCP, or Azure)
• Proficiency in Python (preferred) or similar OO language.
• Experience utilizing Large (or Small) Language Models within software systems.
• Excellent written and verbal communication skills with the ability to articulate comp