Machine Learning Engineer (L3)

See yourself at Twilio

Join the team as Twilio’s next Machine Learning Engineer (L3) on the Data Services and Throughput team.

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 global company that actively opposes racism and all forms of oppression and bias. At Twilio, we support diversity, equity & inclusion wherever we do business.

About the job

This position is needed to to drive the innovation and creation of cutting-edge products that serve the needs of developers, builders, and operators. You will be a crucial bridge between Product and Design, tasked with developing, evaluating and maintaining scalable Machine Learning models within low-latency for real-time applications. Your collaboration and expertise will be fundamental in delivering robust solutions that power our users' success. You will be closely working with a cross-functional team of engineers, architects, product, UI/UX and partners to develop ML and data driven algorithm aspects of customer facing products in Twilio Communication applications.  

Twilio Communications is the leading software for sending messages programmatically. The Data Services and Throughput organization builds AI-enabled capabilities that separate Twilio from its competitors in messaging capabilities.  

Responsibilities

In this role, you’ll:

• Build and maintain scalable, high quality machine learning solutions in production
• Design and implement tools and procedures to evaluate performance and accuracy of models and data.  
• 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 “why” behind models & systems and develop high quality ML-based software at scale
• Truly own the product you work on. Be responsible for SLA, on call, incident resolution, customer feedback, and participate in blameless post-mortems to make our products better.
• Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements and define the scope of the systems and leverage state-of-the-art Statistics, Machine Learning, Deep Learning and Gen AI to address the business problems.
• Drive high engineering standards on the team through code review, automated testing, and mentoring.
• Collaborate and brainstorm product ideas with product managers, designers, and engineers.

Qualifications