Principal Machine Learning & Data Engineer

Details

• 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.
• 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.
• Graduate degree focused on machine learning, distributed systems, or applied statistics.
• Contributions to open-source ML or data infrastructure projects.
• Experience with privacy-enhancing technologies (differential privacy, homomorphic encryption) or on-device inference.
• Background in conversational AI, real-time communications, or large-language-model deployment at scale.
• Exposure to compliance-heavy environments (HIPAA, PCI-DSS) and secure multi-tenant design patterns.
• Published research, patents, or conference talks in ML systems or data engineering.
• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $184,500 - $230,700.
• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $195,300 - $244,200.
• Based in the San Francisco Bay area, California: $217,000 - $271,300.
• This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.