Staff Machine Learning Engineer

See yourself at Twilio

Join the team as our next Staff Machine Learning Engineer.

Who we are & why we’re hiring

Twilio powers real-time business communications and data solutions that help companies and developers worldwide build better applications and customer experiences.

Although we're headquartered in San Francisco, we have presence throughout South America, Europe, Asia and Australia. We're on a journey to becoming a globally anti-racist, anti-oppressive, anti-bias company that actively opposes racism and all forms of oppression and bias. At Twilio, we support diversity, equity & inclusion wherever we do business. We employ thousands of Twilions worldwide, and we're looking for more builders, creators, and visionaries to help fuel our growth momentum.

About the job

Twilio Engage is the brand-new growth automation platform, built natively on Segment as the customer data platform (CDP) and natively on Twilio’s communications APIs. Our vision is a unified platform that thoughtfully delivers the most relevant content to marketers through the best channel at every point in their lifecycle.

We are building an intelligent customer engagement platform by leveraging the data across multiple channels and harnessing the power of machine-learning. We are personalizing customer engagement by transforming raw customer data across all channels into actionable, individualized, machine-learning based customer predictions that marketers can demonstrate in any workflow or process.

Responsibilities

In this role, you’ll:

• Build and maintain scalable machine learning solutions in production
• Train and validate both deep learning-based and statistical-based models considering complexity, performance, and robustness
• Work closely with software engineers, build tools to enhance productivity and to ship and maintain ML models
• Demonstrate end-to-end understanding of applications and develop a deep understanding of the “why” behind our models & systems
• Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements and define the scope of the systems needed
• Drive high engineering standards on the team through code review, automated testing, and mentoring.

Qualifications 

Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also 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:

• 5+ years of applied ML experience.
• Strong background in the foundations of machine learning and building blocks of modern deep learning.
• Proficiency in Python (preferred) or similar OO language.
• Track record of building, shipping and maintaining machine learning models in production in an ambiguous and fast paced environment.
• Track record of designing and architecting large scale experiments and analysis to inform product roadmap.
• Familiarity with ML Ops concepts related to testing and maintaining models in production such as testing, retraining, and monitoring.
• Demonstrated ability to ramp up, understand, and operate effectively in new application / business domains.

Desired:

• Experience with Large Language Models
• Understanding of embedding approaches
• Experience with uplift modeling, causal inference or contextual bandits.

Location 

This role will be remote, and based in the USA.

Approximately <10% travel is anticipated. 

What We Offer

There are many benefits to working at Twilio, including, in addition to competitive pay, things like generous time-off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Twilio thinks big. Do you?

We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic. Additionally, we empower employees to build positive change in their communi