About the Job
At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences.
Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences th...
We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!
Key Responsibilities
In this role, you’ll:
Build out new functionality within a fast moving product seeing rapid adoption.
Take a nebulous idea, design a rigorous experiment, and execute it within weeks.
Conduct deep-dive research into state-of-the-art LLM orchestration, retrieval strategies, and data-driven personalization.
Build ML systems that hold up at Twilio scale.
Rapidly acquire new technical skills and knowledge in a fast-paced, high-delivery environment.
Proactively leverage and integrate the latest AI development stacks to bypass boilerplate engineering and focus on core differentiation.
Required Skills & Abilities
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!
5+ years applied ML/AI experience with a track record of owning technically ambitious systems end to end rather than contributing to someone else's design.
Comfort operating in a 0-to-1 setting with ambiguous requirements and a strong bias for action.
Proficiency in Python programming language.
Experience building cloud-based services on AWS, GCP, or Azure, with high-volume data, streaming or real-time inference paths, and a range of data stores.
Deep expertise in the design, architecture, and deployment of production-grade ML/AI systems, including LLM orchestration, embedding models, and vector stores.
Strong fundamentals of statistical machine learning algorithms, transformer models, LLMs
Ability to raise the technical bar of a team through mentorship, design review, and standards, without formal management authority.
Experience in building cloud-based services using AWS, GCP, or Azure.
Strong communication skills and highly effective collaborator who works well with teammates.
Prior experience building autonomous agents that handle multi-turn conversations and maintain long-term context/consistency.
Strong background in predictive modeling on user behavior, including experiment design and the causal or counterfactual methods needed when randomization is partial.
Prior experience working in a globally distributed team.
