Principal Machine Learning Engineer

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ABOUT THE ROLE

There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting.

Our first application is an agent-first mobile communication app. We believe building applications that users use daily for communication, coordination and collaboration needs will help integrate AI into their lives. The net effect is to eliminate misinformation, achieve low coordination costs, enable high quality tasks and collaboration at scale with minimal or little prompting.

As Principal Machine Learning Engineer, you own the execution layer of our intelligence, turning research and model capabilities into reliable, scalable production systems.

You will work across the model lifecycle: data, training, evaluation, inference, and deployment. This is a hands-on leadership role for someone who wants to operate at the intersection of research, systems, and product.

WHAT YOU'LL OWN

• Own the end-to-end ML systems powering our company, from data and training to evaluation, inference, and deployment.

• Build and evolve training and fine-tuning pipelines for large models.

• Design evaluation systems that measure capability, robustness, safety, and real-world product performance.

• Architect high-performance inference systems, optimizing latency, GPU utilization, memory, cost, and reliability.

• Build data pipelines and systems for high-quality real-world and synthetic training data.

• Establish reliable production infrastructure for deploying, monitoring, and continuously improving models.