Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!
15+ years of experience in software engineering, with at least 6+ years specifically focused on building and scaling production-grade ML systems at a platform level
Extensive experience with ML Ops and LLM Ops patterns, including designing and implementing rigorous evaluation metrics, automated retraining loops, and monitoring for non-deterministic AI features at scale
Deep expertise in the design, architecture, and deployment of production-grade ML/AI systems, including deep knowledge of transformer models, LLM orchestration, embedding models, inference optimization and vector stores
Deep understanding of the Context Engineering lifecycle, including semantic retrieval, contextual compression, state management across multi-turn conversations
Strong background in building cloud-based services using AWS, GCP, or Azure, with experience managing high-volume data and various data stores
Exceptional communication and collaboration skills, with a proven ability to mentor engineers, influence company wide technical strategy, product direction, and drive results across the company
A Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a closely related quantitative field
A track record of relevant publications at top ML conferences or significant open-source contributions
Experience designing evaluation frameworks that specifically measure context quality
Track record of designing and implementing enterprise-scale ML/AI Ops platforms
Experience working in a geographically distributed environment
Location
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