Staff Machine Learning Engineer Job in Twilio

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. Twilio is looking for a Staff Machine Learning engineer to join the rapidly growing Comms Platform Engineering team of our Messaging business unit. You will understand the needs of our customers and build data products that solve their needs at a global scale. Working side by side with other engineering teams and product counterparts, you will 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 the entire Twilio organization 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 Work closely 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 Drive engineering best practices around code reviews, automated testing and monitoring 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: 7+ years of applied ML experience. Proficiency in Python is preferred. We will also consider strong quantitative candidates with a background in other programming languages 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 Experience of working on AWS