Staff Machine Learning Engineer, L4

🕒 July 6

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Twilio

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Millions of developers around the world have used Twilio to unlock the magic of communications to improve any human experience.Twilio has democratized communications channels like voice, text, chat, video, and email by virtualizing the world’s communications infrastructure through APIs that are simple enough for any developer to use, yet robust enough to power the world’s most demanding applications.By making communications a part of every software developer’s toolkit, Twilio is enabling innovators across every industry — from emerging leaders to the world’s largest organizations — to reinvent how companies engage with their customers.Founded in 2008, Twilio has over 5,000 employees in 26 offices in 17 countries and counting, with headquarters in San Francisco and other offices in Atlanta, Bangalore, Berlin, Bogotá, Denver, Dublin, Paris, Prague, Hong Kong, Irvine, London, Madrid, Munich, Malmö, Mountain View, Redwood City, New York City, São Paulo, Sydney, Melbourne, Singapore, Tallinn, and Tokyo.

📋 Description

• 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

🎯 Requirements

• 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 • Experience of working on AWS

🏖️ Benefits

• Competitive pay • Generous time off • Ample parental and wellness leave • Healthcare • Retirement savings program