Jobs at Pika

Design and build scalable backend and infrastructure for autonomous AI agents: real-time messaging, agent runtimes, LLM integrations, vector retrieval, APIs, databases, and production reliability while mentoring engineers and driving architectural decisions.

Contribute to large-scale pre-training and optimization of Videogen models, design and prototype high-throughput video/multimedia data pipelines, collaborate with researchers and engineers, and apply research techniques to production-scale generative video systems.

Lead end-to-end product launches for creator-focused AI, develop positioning and messaging, coordinate cross-functional launch plans (content, social, PR, community), partner with product and research to translate technical features, and measure launch performance to inform future campaigns.

Lead end-to-end product development for a flagship generative AI creative platform: own roadmap, define success metrics, collaborate with engineering/design/research, talk to creators, write specs, and launch transformative features that expand creative possibilities.

Own growth for a consumer creative AI product—drive acquisition, activation, retention, and monetization through rapid experimentation, analytics, and cross-functional execution. Launch and analyze A/B tests, build retention loops, develop metrics and dashboards, and collaborate with engineering, design, marketing, and data to scale user creativity and engagement.

Design, build, and own large-scale data pipelines and ML data curation for multimodal (text, image, audio, video) model training. Partner with research teams to ingest, label, filter, augment, store, and ensure dataset quality, compliance, and scalability. Optimize distributed data processing for training, prototype dataset tools, and integrate research advances into production systems.

Lead architecture and delivery of user-facing product features for web and multi-platform apps. Own projects end-to-end, build scalable real-time collaboration systems, integrate generative AI workflows, collaborate with product/design, mentor engineers, and drive technical excellence.

Lead architecture and implementation of scalable backend systems, distributed infrastructure, and APIs. Own large-scale projects from design to launch, enable low-latency real-time collaboration, integrate generative AI features, drive backend best practices, mentor engineers, and ensure reliability, performance, and security across products.

Lead inference acceleration and GPU-parallelism optimizations (TP, SP, PP); implement high-performance CUDA/NCCL kernels; deploy videogen and LLM models to production; collaborate with researchers, conduct code reviews, mentor engineers, and optionally improve training efficiency and resource utilization.