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