Machine Learning Engineer

Summary

Join Twilio as a Senior Machine Learning Engineer (L3) and contribute to the development and deployment of machine learning systems for our Comms Platform Engineering team. You will collaborate with product and engineering teams to execute the roadmap for Twilio’s AI/ML products and services, building data products that solve customer needs at a global scale. This role requires a strong background in ML engineering and a proven track record of solving data and machine-learning problems at scale. You will work closely with various teams, own end-to-end execution of ML solutions, and drive engineering best practices. The position is remote-based in India (specific locations listed) with occasional travel required. Twilio offers competitive benefits, including generous time off, parental and wellness leave, healthcare, and a retirement savings program.

Requirements

• 5+ 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
• 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 some of the modern data storage, messaging, and processing tools (Kafka, Apache Spark, Hadoop, Presto, DynamoDB etc.)
• Experience working in an agile team environment with changing priorities
• Experience of working on AWS

Responsibilities

• 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 engineering best practices around code reviews, automated testing and monitoring

Preferred Qualifications

Experience with Large Language Models

Benefits

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