Principal, Machine Learning Engineer (L5)

Hiring and how we work

See yourself at Twilio

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

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.

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 and knowledge in a fast-paced, high-delivery environment.
• Proactively leverage and integrate the latest AI development stacks to bypass boilerplate engineering and focus on core differentiation.
• 10+ years applied ML/AI experience with a track record of owning technically ambitious systems end to end rather than contributing to someone else's design.
• Comfort operating in a 0-to-1 setting with ambiguous requirements and a strong bias for action.
• Proficiency in Python programming language.
• Experience building cloud-based services on AWS, GCP, or Azure, with high-volume data, streaming or real-time inference paths, and a range of data stores.
• Deep expertise in the design, architecture, and deployment of production-grade ML/AI systems, including LLM orchestration, embedding models, and vector stores.
• Strong fundamentals of statistical machine learning algorithms, transformer models, LLMs
• Ability to raise the technical bar of a team through mentorship, design review, and standards, without formal management authority.
• Experience in building cloud-based services using AWS, GCP, or Azure.
• Strong communication skills and highly effective collaborator who works well with teammates.
• Prior experience building autonomous agents that handle multi-turn conversations and maintain long-term context/consistency.
• Strong background in predictive modeling on user behavior, including experiment design and the causal or counterfactual methods needed when randomization is partial.
• Prior experience working in a globally distributed team.

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