🛠 Tech Stack

💼 About This Role

You'll design and build cloud-native ML infrastructure for Twilio's Trust Intelligence Platform, powering real-time intelligence from customer interactions. Your work will directly enable product teams to move from raw events to actionable insights. This role offers clear technical ownership and mentoring in a company shaping the future of communications with AI.

🎯 What You'll Do

• Architect scalable data pipelines and feature stores for batch and real-time workloads.
• Build reproducible ML training and inference workflows using MLOps tooling.
• Integrate event streams from Twilio products into analytics-ready datasets.
• Monitor and improve data quality, model performance, latency, and cost.

📋 Requirements

• B.S. in CS, Data Engineering, or related field or equivalent experience.
• 4-8 years building and operating data or ML systems in production.
• Proficient in Python and SQL with software engineering fundamentals.
• Hands-on experience with ETL/ELT orchestration tools and cloud data warehouses.

✨ Nice to Have

• Experience with Twilio Segment, Kafka/Kinesis, or high-throughput event buses.
• Exposure to infrastructure-as-code (Terraform, Pulumi) and GitHub CI/CD.
• Knowledge of generative AI workflows or vector databases.

🎁 Benefits & Perks

• 🏖️ Generous time off including paid sick time and personal time off.
• 👶 Ample parental and wellness leave.
• 🏥 Health care insurance coverage.
• 💰 Retirement savings program (401(k)).
• 📈 Equity plan and corporate bonus plan eligibility.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Chat· 45 min