Machine Learning Engineer

Stack

Responsibilities

• ▹Design and develop 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 model development, validation and deployment, with guidance from senior engineers on complex architectural decisions
• ▹Instrument AI/ML services with metrics, logging, and telemetry to monitor model performance and operational health against SLOs
• ▹Participate in on-call rotations, executing progressive rollouts and applying mitigation strategies to keep production inference services healthy
• ▹Collaborate across planning, design, and code review phases, contributing to product and technical discussions and helping raise code quality through review feedback

Requirements

• ▹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 a similar OO language
• ▹Experience utilizing large (or small) language models within software systems
• ▹Excellent written and verbal communication skills with the ability to articulate complex technical concepts to technical and non-technical audiences

Soft skills

About the company

Twilio delivers innovative communications solutions to hundreds of thousands of businesses and empowers millions of developers to craft personalized customer experiences, with a remote-first culture.