Staff Machine Learning Engineer

Overview

Staff Machine Learning Engineer on Twilio's AI/ML Platform team, building the foundational AI/ML capabilities and common platform tooling that power intelligent engagement experiences across Twilio.

What you'll do

• Conduct deep-dive research into and implement state-of-the-art LLM inference and orchestration.
• Identify opportunities to leverage small language models via fine-tuning/distillation.
• Build ML systems that hold up at Twilio scale.
• Set standards and tooling for building evals across a range of AI/ML capabilities.
• Influence the design and evolution of the company-wide ML/AI Ops foundation, ensuring every AI capability incorporates rigorous offline and online evals.
• Drive improvements to managing LLM workloads across the company, while ensuring easy and compliant access to data for AI/ML exploration and product development.
• 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.

What you'll need

• 8+ 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.
• Strong fundamentals of statistical machine learning algorithms, transformer models, LLMs.
• Extensive experience with ML Ops and LLM Ops patterns, including designing and implementing rigorous evaluation metrics for non-deterministic AI features at scale.
• Strong communication skills and highly effective collaborator who works well with teammates.
• Familiarity with AI-assisted development tools (e.g., Claude, Codex, GitHub Copilot, Cursor, etc.).

Nice to have

• Prior experience building evals for autonomous agents and large language models.
• Prior experience building autonomous agents that handle multi-turn conversations and maintain long-term context/consistency.
• Prior experience working in a globally distributed team.
• Evidence of technical leadership/impact, such as contributions to open-source data/ML projects and/or published technical presentations, blog posts, papers, or research.

Details

• Remote, based in Ontario, British Columbia or Alberta, Canada.
• May be required to travel occasionally for project or team in-person meetings.
• May be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings.
• Employment type not stated.