VP of Research, Machine Learning

About A1 There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time. Role You will own the research and intelligence direction of this system. Your role is to define how AI reasons, evaluates, and improves in a product used with high frequency. What You'll Do Set and evolve the research direction for A1’s core intelligence, including context representation, memory, reasoning, planning, and orchestration. Decide when to design new model architectures versus adapting or leveraging frontier open-source or commercial models. Define evaluation frameworks that measure real-world usefulness, robustness, safety, and long-term behavior – not benchmark vanity. Own alignment, safety, and guardrail strategy as first-class product concerns. Guide exploration of frontier techniques such as: retrieval-augmented training mixture-of-experts distillation multi-agent orchestration multimodal systems Shape early product intelligence direction in close partnership with product and application engineering. Set the technical bar for research rigor, judgment, and taste across the organization. Requirements Deep experience building or evolving real machine learning systems used in production. Strong technical judgment around model behavior, failure modes, and long-horizon trade-offs. A builder’s mindset: you care about systems that work in the real world, not just ideas. Comfortable making irreversible or high-impact deci