Machine Learning & Data Engineer

<h3>📋 Description</h3> • Twilio’s next L5 Machine Learning & Data Engineer to lead the design, build, and operation of the internal ML-and-data platform that powers every customer interaction. You will architect cloud-native pipelines, model-serving infrastructure, and developer tooling that allow Twilio’s product teams to iterate rapidly and safely at scale, advancing our mission to unlock the imagination of builders. • Responsibilities: • 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. <h3>🎯 Requirements</h3> • 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. <h3>🏖️ Benefits</h3> • health care insurance • 401(k) retirement account • paid sick time • paid personal time off • paid parental leave • This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan.