Machine Learning Engineer (L3)

Overview

Build foundational AI/ML capabilities for Twilio’s Customer Memory Team, powering intelligent engagement experiences and contextual intelligence for customers. Lead rapid research cycles across theoretical research, production-grade experimentation and enterprise-quality software.

What you'll do

• Build new functionality within a fast-moving product seeing rapid adoption.
• Turn nebulous ideas into rigorous experiments and execute them 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.
• Leverage and integrate the latest AI development stacks to bypass boilerplate engineering and focus on core differentiation.

What you'll need

• 5+ years of 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 and LLMs.
• Ability to raise the technical bar of a team through mentorship, design review and standards, without formal management authority.
• Strong communication skills and ability to collaborate effectively with teammates.

Nice to have

• 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.

Details

• Remote role based in India: Karnataka, Tamil Nadu, Telangana State, Maharashtra and New Delhi.
• Occasional travel may be required for project or team in-person meetings.