Twilio is a Platform-as-a-Service (PaaS) company established in 2007. In support of a flexible workplace, Twilio has previously posted freelance, flexible sched
Principal Machine Learning, Data Engineer
Location
California + 5 moreAll locations: California | Connecticut | New Jersey | New York | Pennsylvania | Washington
Posted
57 days ago
Salary
$184.5K - $230.7K / year
Seniority
Lead
Job Description
Principal Machine Learning, Data Engineer
Twilio
• 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.
Job 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
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