Own full-cycle recruiting from sourcing through closing, partnering with hiring managers and leadership to build pipelines, deliver a strong candidate experience, and improve recruiting processes.
Pika jobs
A creative platform for generating video, images, and audio with AI models.
12 open roles at Pika
Research Scientist, Post-Training β Video Generation
Own RL post-training and reward-model development for large-scale video generation models, leading alignment evaluation and helping distill tuned models into efficient samplers.
Own product design and direction for pika.artβs web app, shaping creative tools and growth experiences from specs and prototypes through implementation, QA, and launch.
Design and scale data infrastructure for an AI creative platform, building reliable pipelines and analytics systems while enabling data-driven product, engineering, and machine learning work.
Build and optimize product features, experiments, and growth systems that improve user acquisition, activation, engagement, and retention across an AI creative platform.
Lead product engineering strategy, architecture, and execution across user-facing products, scaling engineering teams and delivering reliable, high-performing systems in close partnership with product, design, and ML leaders.
Leads the technical vision, architecture, and delivery of user-facing creative products, including real-time collaboration and generative AI features, while shaping scalable systems and mentoring engineering teams.
Build and scale end-to-end product features for AI-powered creative tools, shaping user-facing experiences from concept to launch while guiding technical quality, architecture, and team practices.
Own the roadmap and lead product initiatives from concept to launch, partnering with engineering, design, and research to shape intuitive generative AI tools for creators and measure their impact.
Architect and scale data infrastructure for multimodal model training, owning large-scale pipelines and dataset curation while partnering with research and engineering teams to improve data quality and reliability.
Lead the design and delivery of scalable backend systems, APIs, and cloud infrastructure powering AI-driven products, real-time collaboration, and reliable experiences for millions of users.
Optimize inference pipelines and GPU performance for video and language models, applying acceleration techniques and distributed parallelism to bring advanced AI systems into production at scale.
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