Principal, Machine Learning Engineer (L5)

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. .

Hiring and how we work

We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!

Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. .

See yourself at Twilio

Join the team as our next Principal Machine Learning Engineer in Twilio’s Customer Memory Team.

About the job

In this role, you will build the foundational AI/ML capabilities that power intelligent engagement experiences for Twilio customers - letting any application, human or AI agent, or channel know who a customer is, what they have done, and how best to reach them.

This role requires a builder and curious mindset, someone who can bridge the gap across theoretical research, production-grade experimentation and enterprise quality software. You will lead rapid research cycles to solve complex problems regarding contextual intelligence and large scale ML problems ensuring every interaction feels seamless and personalized.

Responsibilities

In this role, you’ll

• Build out new functionality within a fast moving product seeing rapid adoption.
• Take a nebulous idea, design a rigorous experiment, and execute it within weeks.
• Conduct deep-dive research into state-of-the-art LLM orchestration, retrieval strategies, and data-driven personalization.
• Build ML systems that hold up at Twilio scale.
• Rapidly acquire new technical skills