Staff Machine Learning Engineer
Job Description
Who we are
At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences.
Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands.
We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!
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See yourself at Twilio
Join the team as Twilio’s next L4, Machine Learning Engineer, Trust Intelligence Platform
About the job
Join Twilio’s rapidly-growing Trust Intelligence Platform team as an L4 Machine Learning. You will design, build, and operate the cloud-native data and ML infrastructure that powers every customer interaction, enabling Twilio’s product teams and customers to move from raw events to real-time intelligence. This is a hands-on, builder-focused role that offers clear technical ownership, mentoring, and growth inside a company defining the future of communications with AI.
Responsibilities
In this role, you’ll:
- Architect, implement, and maintain scalable data pipelines and feature stores for batch and real-time workloads.
- Build reproducible ML training, evaluation, and inference workflows using modern orchestration and MLOps tooling.
- Integrate event streams from Twilio products (e.g., Messaging, Voice, Segment) into unified, analytics-ready datasets.
- Monitor, test, and improve data quality, model performance, latency, and cost.
- Partner with product, data science, and security teams to ship resilient, compliant services.
- Automate deployment with CI/CD, infrastructure-as-code, and container orchestration best practices.
- Produce clear documentation, dashboards, and runbooks; share knowledge through code reviews and brown-bag sessions.
- Embrace Twilio’s “We are Builders” values by taking ownership of problems and drivi
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