Job Opportunities API

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 best practices around code reviews, automated testing and monitoring 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: 7+ years of applied ML experience with proficiency in Python Strong background in the foundations of Machine Learning and building blocks of modern Deep Learning 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. You have a clear understanding of frameworks like - PyTorch, TensorFlow, or Keras, why and how these frameworks do what they do 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. You’ve explored modern data storage, messaging, and processing tools (Kafka, Apache Spark, Hadoop, Presto, DynamoDB etc.) and demonstrated experience designing and coding in big-data components such as DynamoDB or similar Experience working in an agile team environment with changing priorities Exp