Staff Machine Learning Engineer

See yourself at Twilio

Join the team as Twilio’s next Staff Machine Learning Engineer on Twilio’s AI/ML Platform team.

About the job

We are actively recruiting for this role to fill an existing vacancy. This position is needed to build the foundational AI/ML capabilities and common platform tooling that power intelligent engagement experiences across Twilio. You will influence the design and evolution of our company-wide ML/AI Ops foundation, ensuring every AI capability incorporates rigorous offline and online evals to maintain exceptionally high quality.

You will drive improvements to managing LLM workloads across the company, while ensuring easy and compliant access to data for AI/ML exploration and product development. This role requires a builder mindset to bridge theoretical research, production-grade experimentation, and scalable, enterprise-quality software.

Responsibilities

In this role, you’ll:

Conduct deep-dive research into and implement state-of-the-art LLM inference and orchestration.

Identify opportunities to leverage small language 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.

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.

Qualifications

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

*Required:

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.).

Desired:

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.

Location

This role will be remote and based in Ontario, British Columbia or Alberta, Canada.

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Based on role, employees may also be eligible for additional compensation and benefits, including but not limited to incentive programs, commissions, equity grants, health and wellness benefits, retirement contributions, and paid time off.

The estimated pay ranges for this role are as follows:

$160,320 - $200,400

Target Bonus Percentage 12.5%

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.