Principal Machine Learning, Data Engineer

🕒 April 9

🏄 California, Connecticut, +4 more states – Remote

🏄 California – Remote 🦌 Connecticut – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🔔 Pennsylvania – Remote ☕ Washington – Remote

💵 $184.5k - $230.7k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

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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

• Architect and evolve Twilio’s end-to-end ML and real-time data platforms for reliability, security, and cost efficiency. • Design scalable feature stores, streaming and batch pipelines, and low-latency model-serving layers on AWS. • Implement MLOps best practices—automated testing, CI/CD, monitoring, and rollback—for hundreds of daily deployments. • Own system design reviews, threat modeling, and performance tuning for high-volume communications workloads. • Lead cross-functional engineering efforts, breaking down complex initiatives into executable roadmaps. • Mentor staff and senior engineers, raising the technical bar through code reviews and pair programming. • Partner with Product, Security, and Compliance to meet stringent privacy and governance requirements (HIPAA, SOC 2, GDPR). • Champion a culture of experimentation, data-driven decision-making, and continuous improvement.

🎯 Requirements

• Bachelor’s or higher in Computer Science, Engineering, Mathematics, or equivalent practical experience. • 7+ years building and operating production data or machine-learning systems at scale. • Expert fluency in Python and one compiled language (Java, Scala, Go, or C++). • Hands-on mastery of distributed data frameworks (Spark/Flink), SQL/NoSQL stores, and streaming platforms (Kafka/Kinesis). • Demonstrated success designing cloud-native architectures on AWS, including Terraform-managed infrastructure. • Deep knowledge of container orchestration (Kubernetes/EKS), service-mesh networking, and autoscaling strategies. • Practical experience implementing MLOps tooling such as MLflow, Kubeflow, SageMaker, or Vertex AI. • Strong grasp of model-lifecycle concerns—feature engineering, offline/online parity, A/B testing, drift detection, and retraining. • Proven ability to lead technical projects end-to-end and influence without authority across multiple teams. • Exceptional written and verbal communication skills, with a bias toward clarity and action.

🏖️ Benefits

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