Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences
Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands
We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!
See yourself at Twilio Join the team as Twilio’s next Staff Machine Learning Engineer
About the job This position is needed to scope, design, and deploy machine learning systems into the real world, the individual will closely partner with Product & Engineering teams to execute the roadmap for Twilio’s AI/ML products and services
You will understand customers need, build data products that works at a global scale and own end-to-end execution of large scale ML solutions
To thrive in this role, you must have a deep background in ML engineering, and a consistent track record of solving data & machine-learning problems at scale. You are a self-starter, embody a growth attitude, and collaborate effectively across organizations
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 use-case, complexity, performance, and robustness 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 Work closely with data platform teams to build robust scalable batch and realtime data pipelines Collaborate with software engineers, build tools to enhance productivity and to ship and maintain ML models Drive high engineering standards on the team through mentoring and knowledge sharing Uphold engineering