Machine Learning Engineer (L3)

About this job

As a Machine Learning Engineer (L3) at Twilio in India, you will focus on building foundational AI and ML capabilities for the Customer Memory Team. Your day-to-day work involves designing and executing rapid experiments, conducting deep-dive research into LLM orchestration and retrieval strategies, and developing scalable machine learning systems. You will bridge the gap between theoretical research and production-grade software to power intelligent engagement experiences for customers across various applications and AI agents. Twilio operates as a remote-first company in India, empowering developers and businesses globally while fostering a connected and inclusive team environment.

Responsibilities

• 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.

Requirements

• 5+ years applied ML/AI experience owning technically ambitious systems end to end.
• 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.
• 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.
• Strong communication skills and effective collaboration abilities.

Good to have

• Prior experience building autonomous agents that handle multi-turn conversations and maintain long-term context.
• Strong background in predictive modeling on user behavior, including experiment design and causal methods.
• Prior experience working in a globally distributed team.

Who should apply

This role suits experienced machine learning professionals with at least 5 years of applied ML/AI experience who excel in ambiguous 0-to-1 settings. Candidates should have a strong background in Python, cloud services, and production-grade AI systems like LLMs and vector stores. Because the posting specifies a requirement of 5+ years of experience, freshers are not eligible to apply for this particular position.

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