Staff ML Engineer: Build Scalable AI Systems (Remote)

Twilio Inc.

United States

Remote

USD 180,000 - 240,000

Full time

4 days ago
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Benefits offered by this job

Competitive pay
Generous time off
Parental leave
Wellness leave
Healthcare
Retirement savings

Job summary

Twilio is seeking a Staff Machine Learning Engineer on the Conversation Memory team to build foundational AI/ML capabilities powering intelligent engagement for customers. You will lead research-to-production cycles, bridging theory and scalable software in a remote-first environment.

Join a globally distributed team, own technically ambitious systems end-to-end, and mentor others while delivering high-volume, real-time inference work across platforms.

Qualifications

  • 8+ years of applied ML/AI experience with end-to-end ownership of systems.
  • Proficiency in Python and cloud-based services with large-scale data.
  • Strong communication and collaboration in a globally distributed team.
  • Experience with autonomous agents and multi-turn conversations is desirable.

Responsibilities

  • Build new functionality within a fast moving product with rapid adoption.
  • Design rigorous experiments and execute them within weeks.
  • Research state-of-the-art LLM orchestration, retrieval strategies, and data-driven personalization.
  • Build ML systems that scale to Twilio’s needs.
  • Rapidly acquire new technical skills in a fast-paced environment.
  • Leverage latest AI stacks to focus on core differentiation.

Skills

Applied ML/AI
Python
AWS
GCP
Azure
LLMs
Transformer models

Tools

AWS
GCP
Azure

Job description

Twilio is seeking a Staff Machine Learning Engineer on the Conversation Memory team to build foundational AI/ML capabilities powering intelligent engagement for customers. You will lead research-to-production cycles, bridging theory and scalable software in a remote-first environment.

Join a globally distributed team, own technically ambitious systems end-to-end, and mentor others while delivering high-volume, real-time inference work across platforms.

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