AI creative tools. Built for Creatives. Backed by Lightspeed and AI Grant.
About the role
At Pika, we are pioneering the next generation of creative infrastructure built around real-time, multimodal generation and intelligent agentic platforms. We are seeking Research Scientists with expertise in RL post-training and generative modeling for large-scale video generation. The focus is on refining Pika's video generation models using RL alignment and building robust video reward models. This is a staff and lead-level opportunity.
What they're looking for
- 2+ years hands-on research experience in post-training or generative modeling
- RL or preference-optimization experience on generative models with evidence of model improvement
- Strong grounding in diffusion or flow-matching models, PyTorch, and multi-node distributed training
More about this role
At Pika, we are pioneering the next generation of creative infrastructure built around real-time, multimodal generation and intelligent agentic platforms. We are seeking Research Scientists with expertise in RL post-training and generative modeling for large-scale video generation. The focus is on refining Pika's video generation models using RL alignment and building robust video reward models. This is a staff and lead-level opportunity.
As a key member of our research team, you will own RL-based post-training for video diffusion/flow-matching models, develop state-of-the-art reward models, and lead post-training evaluation across human and automated metrics. You will collaborate closely with engineering and product teams, shaping the frontier of real-time creative and agentic video platforms.
RL alignment of Pika's video generation models and the reward models that drive them.
Distillation of RL-tuned models is a secondary focus.
Run RL post-training (preference optimization, online RL against learned rewards) for video diffusion/flow-matching models at multi-node scale.
Build video reward models: define target evaluation dimensions, design/configure preference data collection...
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