Machine Learning & Data Engineer, Twilio

• 1–3 years of professional experience in software, data, or ML infrastructure engineering
• Proficiency in Python or Java and in SQL for data manipulation and analysis
• Hands-on experience building ETL/ELT pipelines with tools such as Apache Spark, Flink, or Airflow
• Familiarity with training and deploying ML models using scikit-learn, TensorFlow, or PyTorch
• Working knowledge of containerization (Docker) and at least one major cloud platform (AWS, GCP, or Azure)
• Comfort with Linux, Git, and CI/CD workflows; ability to write clean, tested, maintainable code
• Clear verbal and written communication skills and a demonstrated sense of ownership
• Bachelor’s degree in Computer Science or a related field, or equivalent practical experience
• For this role, you may be required to travel occasionally to participate in project or team in-person meetings

Desirable

• Twilio’s L2 Machine Learning & Data Engineer designs, builds, and maintains the data pipelines, training workflows, and real-time inference services that power AI-driven communications
• You will convert raw interaction data into reliable, scalable systems that internal product teams and external builders trust to prototype, deploy, and measure machine-learning solutions at global scale
• Build and optimize batch and streaming data pipelines processing billions of interaction events per day
• Implement reusable model-training and evaluation workflows on Twilio’s internal ML platform
• Deploy, monitor, and troubleshoot low-latency inference services in Kubernetes and serverless environments
• Automate data-quality checks, feature logging, and lineage tracking to guarantee trustworthy datasets
• Collaborate with product, data-science, and DevOps partners to translate business goals into technical roadmaps
• Contribute to design reviews, code reviews, and documentation to elevate engineering standards
• Instrument systems with metrics, alerts, and dashboards that uphold reliability objectives
• Participate in on-call rotations and continually improve CI/CD pipelines

• Applications for this role are intended to be accepted until 16th August, 2025, but may change based on business needs