About the job
Zoom's AI Incubation team is seeking a Research Scientist to contribute to the next wave of LLM post-training, reinforcement learning, and federated AI innovation. You will join a world-class group of PhDs and applied scientists focused on pushing the boundaries of model alignment, reasoning, and agentic intelligence.
Responsibilities
Conducting frontier research in LLM post-training, reinforcement learning, and federated AI to achieve state-of-the-art reasoning, personalization, and reliability.
Developing and implementing evaluation and benchmarking frameworks for model performance, safety, and user experience across distributed environments.
Contributing to 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.
Participating in a culture of scientific rigor, creativity, and rapid experimentation.
Exploring emerging AI paradigms—from agentic reasoning and multimodal fusion to self-improving federated systems—to continuously advance Zoom's AI frontier.
Qualifications
Minimum
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.
Demonstrate passion for applied AI research that bridges scientific discovery and real-world impact.
Have experience implementing AI research concepts and translating them into practical applications.
Preferred
No preferred qualifications listed.