Jobs at Pika

Lead the company’s finance function across accounting, FP&A, budgeting, treasury, AP/AR, payroll, compliance, reporting, and tax. Build scalable forecasting and financial systems, guide resource allocation and business strategy, support fundraising and investor reporting, manage audits and controls, and provide financial insights to executive leadership and the board.

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.

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 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.

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.

Lead end-to-end sales and account management, develop and execute go-to-market strategies, build client relationships, collaborate with product and marketing, and set performance metrics to drive adoption and revenue.

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.