VP of Research, Machine Learning
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The role
Lead the research and intelligence strategy for a proactive, context-aware AI system that maintains context across conversations and carries work forward over time.
Define and evolve core intelligence capabilities: context representation, memory, reasoning, planning, and orchestration.
Decide when to design new architectures versus leveraging frontier models and open-source or commercial options.
Create evaluation frameworks focused on real‑world usefulness, robustness, safety, and long-term behavior, not vanity metrics.
Own alignment, safety, and guardrails as first-class product concerns while exploring techniques like retrieval-augmented training, mixture-of-experts, distillation, multi-agent orchestration, and multimodal systems.
Work hands-on with product and engineering, set high technical standards, and maintain founder-level ownership and urgency to deliver measurable impact.
Define and evolve core intelligence capabilities: context representation, memory, reasoning, planning, and orchestration.
Decide when to design new architectures versus leveraging frontier models and open-source or commercial options.
Create evaluation frameworks focused on real‑world usefulness, robustness, safety, and long-term behavior, not vanity metrics.
Own alignment, safety, and guardrails as first-class product concerns while exploring techniques like retrieval-augmented training, mixture-of-experts, distillation, multi-agent orchestration, and multimodal systems.
Work hands-on with product and engineering, set high technical standards, and maintain founder-level ownership and urgency to deliver measurable impact.
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