VP of Research, Machine Learning
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The role
Own the research and intelligence direction for a proactive AI system, focusing on how it reasons, evaluates, and improves in production.
Set and evolve the research roadmap across 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 prioritizing real-world usefulness, robustness, safety, and long-term behavior—not just benchmarks.
Own alignment, safety, and guardrail strategy as core product concerns, exploring techniques such as retrieval-augmented training, mixture-of-experts, distillation, and multi-agent orchestration.
Partner with product and engineering to shape early product intelligence and elevate the organization’s standards for research rigor, judgment, and practical impact.
Set and evolve the research roadmap across 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 prioritizing real-world usefulness, robustness, safety, and long-term behavior—not just benchmarks.
Own alignment, safety, and guardrail strategy as core product concerns, exploring techniques such as retrieval-augmented training, mixture-of-experts, distillation, and multi-agent orchestration.
Partner with product and engineering to shape early product intelligence and elevate the organization’s standards for research rigor, judgment, and practical impact.
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