Jobs at Pika

Design, build, and scale data pipelines, ETL workflows, analytics infrastructure, and machine-learning data systems. Ensure data quality, security, monitoring, and reliability while optimizing storage and processing performance. Collaborate with engineering, product, and analytics teams on data requirements, modeling, schemas, and scalable infrastructure. The role also establishes data engineering best practices and supports a data-driven culture.

Build and optimize growth features, experimentation frameworks, personalization strategies, onboarding flows, and engagement loops for Pika’s AI creative platform. Analyze user data, run A/B tests, improve performance and reliability, and collaborate with product, marketing, design, and data teams to drive acquisition, activation, engagement, retention, referrals, and virality.

Lead the technical vision, architecture, and roadmap for Pika’s web and multiplatform creative products. Design scalable user-facing systems, real-time collaboration, messaging, generative AI workflows, and cross-service observability. Partner with product and design leaders from ideation through launch, while driving architecture reviews, technical excellence, mentorship, and engineering strategy.

Develop and launch scalable, user-facing features for AI-powered video and multimedia tools. Architect end-to-end solutions across backend and frontend systems, ensure quality and reliability, collaborate with design, product, and ML teams, and mentor engineers. The role involves rapid prototyping, experimentation, technical leadership, and shaping Pika’s core creative product.

Lead the strategy, architecture, and execution of product engineering across Pika’s user-facing AI creative products. Manage and scale multiple engineering teams, oversee reliable and scalable systems, define technical roadmaps, guide architecture and technology decisions, and collaborate with product, design, ML, and executive leadership. The role also emphasizes mentorship, engineering quality, cross-functional alignment, and delivery of high-impact web and mobile products.

Research Scientist responsible for RL-based post-training of large-scale video generation models. The role includes preference optimization, online RL, video reward model development, human and automated evaluation, reward-hacking safeguards, and secondary distillation of aligned models. Candidates need experience with generative modeling or post-training, reinforcement learning, diffusion or flow-matching models, PyTorch, and distributed training. Preferred experience includes visual-generation reward models, VLM-based judging, preference data collection, and video-specific temporal and physics failure modes.

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.

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.