Head of AI Incubation

What you can expect

Zoom is seeking an innovative AI research leader to drive the next wave of LLM post-training, reinforcement learning, and federated AI innovation. This is a rare opportunity to lead a world-class group of PhDs and applied scientists focused on advancing model alignment, reasoning, and agentic intelligence.

As Head of AI Incubation, you will shape Zoom's applied AI research strategy in LLM post-training, RLHF/DPO/RLAIF, federated AI, and multimodal intelligence to deliver breakthroughs that redefine human-AI collaboration. You will lead incubation efforts that transform bold research ideas into scalable, productionready systems to power the next generation of Zoom AI Companion experiences.

About the Team

The AI Incubation team has built one of the best-performing federated AI systems in the industry. The team operates at the frontier of LLM post-training, reinforcement learning for agentic AI, multimodal understanding, federated AI, and AI evaluation.

Zoom's federated AI architecture -spanning Anthropic, OpenAI, and Google models- enables privacy-preserving, edge-to-cloud learning that adapts to user context while maintaining enterprise-grade governance. The Incubation team plays a central role in advancing this federated AI leadership, developing new methods for distributed model optimization, personalized prefix learning, and secure collaboration across heterogeneous AI systems.

Zoom AI is also recognized as an industry leader in speech recognition, optical character recognition (OCR), machine translation, and AI summarization, and has set benchmarks for accuracy and performance across these domains. This foundation of excellence fuels the team's mission to incubate transformative ideas that push conventional AI boundaries and accelerate Zoom's leadership in applied AI.

Responsibilities

• Leading new research and development in LLM post-training, reinforcement learning, and federated AI to achieve state-of-the-art reasoning, personalization, and reliability.
• Designing and implementing advanced evaluation and benchmarking frameworks for model performance, safety, and user experience across distributed environments.
• Driving strategic decision-making on model architectures, fine-tuning strategies, and reinforcement learning pipelines across Zoom's federated AI ecosystem.
• Partnering with product and infra teams to translate research prototypes into scalable, production-grade AI systems that leverage edge and cloud collaboration.
• Mentoring and growing a world-class team of researchers and engineers, fostering a culture of scientific rigor, creativity, and rapid experimentation.
• Identifying and incubating emerging AI paradigms-from agentic reasoning and multimodal fusion to self-improving federated systems.

• Have a PhD or advanced degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Demonstrate proven expertise in LLM post-training, RLHF/DPO/PPO, federated learning, or reinforcement learning for reasoning and alignment.
• Have deep understanding of large-scale distributed training systems and experience with PyTorch, Transformers, DeepSpeed, or CUDA.
• Hold a publication or open-source record demonstrating innovation in LLM optimization, federated AI, or agentic intelligence.
• Have experience leading AI research teams and delivering impactful, production-ready AI solutions.
• Demonstrate passion for applied AI research that bridges scientific discovery and real-world impact.