VP of Research, Machine Learning
About The Position
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.
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 decisions with incomplete information.
- Obsession with evaluation, correctness, and how systems behave over time.
- High ownership mentality — you operate as a founder, not a manager.
- Python
- PyTorch / JAX
- GPU-based training and inference system
Nice To Haves
- If you are looking to focus primarily on publishing, incremental benchmarks, or managing a large research organization, this role will not be a fit.
Responsibilities
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Executive
Education Level
No Education Listed
