Staff Machine Learning Engineer @ Twilio

Job Information

Job Description:

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
  • 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!


  • 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


  • Experience with Large Language Models

Experience Level: Senior
Work From: Onsite

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