Senior Manager, Machine Learning

Who we are

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 that make work feel truly rewarding. Your career at Twilio is in your hands.

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See yourself at Twilio

Join the team as Twilio’s next Senior Manager, Machine Learning on Twilio’s Conversation Memory team.

About the job

This position is critical to leveraging Twilio’s massive data ecosystem and communication scale to build foundational platform capabilities for the next generation of conversational AI, specifically by owning the development of 0-to-1 platform features that empower developers to build sophisticated, context-aware customer engagement applications. This is a highly technical, hands-on role, requiring a "player-coach" mentality to actively contribute technical expertise, bridge the gap between theoretical research and production-grade experimentation, and provide strategic direction to the team, rather than being purely a people manager. The leader in this role must demonstrate a strong bias for action, establishing a high-performing engineering setup that enables rapid iteration, experimentation, and deployment of models in this 0-to-1 setting. Furthermore, they will be responsible for working closely with cross-functional stakeholders to translate ambiguous business problems into a clear, prioritized product roadmap and communicate progress and updates to leadership.

Responsibilities

In this role, you’ll

• Collaborate with other engineering teams and cross functional teams to translate ambiguous business problems into a clear, prioritized ML product roadmap for your team.

• Have a 'player-coach' mentality, and contribute hands-on technical expertise while providing strategic direction and mentorship to the team.

• Establish a high-performing engineering setup that enables the team to rapidly iterate, experiment, and deploy models, fostering a culture of operational excellence and close partnership with product and business stakeholders.

• Drive continuous improvement in the team's processes, tooling, and infrastructure to optimize for velocity, quality, and maintainability.

• Actively monitor the ML and AI landscape to ensure the team is continuously up-to-speed on state-of-the-art research, techniques, and tools, promoting their strategic adoption where appropriate.

• Recruit, manage, and develop a diverse and highly-skilled team of Machine Learning Engineers, setting clear goals and expectations, and providing timely and actionable feedback.

• Define and track key performance indicators (KPIs) to measure the impact and success of the team’s ML products, communicating results clearly to leadership and stakeholders.

• Manage project timelines, dependencies, and risks, ensuring timely delivery of