VP of Research, Machine Learning

About the Role

A1 is building a proactive AI system that goes beyond responding to prompts – it maintains context across conversations, plans actions, and carries work forward over time.

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.

• 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.

• 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.

If you are looking to focus primarily on publishing, incremental benchmarks, or managing a large research organization, this role will not be a fit.

• Python

• PyTorch / JAX

• GPU‑based training and inference system