Data & AnalyticsOn-site

Research Scientist, Foundation Model (Video Generation)

Pika · On-site

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Last seen by MeritLog September 12, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from Pika's Ashby job board and last checked it on September 12, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model: On-site
Salary: $185K - $400K
Location: Palo Alto HQ
Occupation: Data Scientists(O*NET 15-2051.00)

Hiring context

How this role compares at Pika

Pika has 10 live roles in MeritLog’s catalog across 7 job families, and 3 of them are in data & analytics. 9 of those listings publish a pay range, a disclosure rate of 90%.

This role's posted range of $185K - $400K sits above 38% of the 8 other Pika roles quoted over the same currency and period.

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd do

Lead research and development on post-training of multimodal foundation models at scale.
Design and prototype novel algorithms and architectures for high-fidelity, real-time multimodal synthesis and interaction across modalities.
Focus on scalable data pipeline curation and model training strategies for broad, diverse, and sensory-rich datasets.
Advance state-of-the-art techniques in diffusion, autoregressive, and other generative models for large-scale post-training and fine-tuning.
Identify, create, and leverage large, high-quality cross-modal datasets.
Bring research advancements into production-ready systems in collaboration with engineering and product teams.
Publish work in top-tier conferences and journals, and clearly communicate research both internally and externally.
Stay at the forefront of foundational model and real-time multimodal AI research.
5+ years of research experience in large-scale post-training of multimodal foundation models (LLMs, VLMs, Audio LMs, or similar), ideally at the staff or lead scientist level.
Track record as a first author on major publications in top conferences or journals (e.g., NeurIPS, ICML, ICLR).
Extensive hands-on experience with large-scale multimodal model design, training, and deployment.
Deep understanding and implementation experience with generative architectures (diffusion, autoregressive, cross-modal, etc.).
Expertise in high-throughput, scalable dataset curation and model pipeline optimization for multimodal applications.
Strong programming and prototyping skills (Python, PyTorch, TensorFlow, etc.) and experience deploying research into production systems.
Excellent communication and collaboration skills, and a passion for building creative enabling technology.

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

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 accomplished Research Scientists in Foundation Models with expertise in post-training large-scale multimodal foundation models to advance our mission of making agentic, real-time generative technology accessible and transformative for millions of creators. This is a staff and lead-level opportunity. As a key member of our research team, you will design and implement core technologies, develop new methodologies for large-scale multimodal post-training (text, image, audio, and video), and drive innovative approaches for foundational model architecture. You will collaborate closely with engineering and product teams, shaping the future of real-time creative and agentic platforms at scale. What You’ll Do - Lead research and development on post-training of multimodal foundation models at scale. - Design and prototype novel algorithms and architectures for high-fidelity, real-time multimodal synthesis and interaction across modalities. - Focus on scalable data pipeline curation and model training strategies for broad, diverse, and sensory-rich datasets. - Advance state-of-the-art techniques in diffusion, autoregressive, and other generative models for large-scale post-training and fine-tuning. - Identify, create, and leverage large, high-quality cross-modal datasets. - Bring research advancements into production-ready systems in collaboration with engineering and product teams. - Publish work in top-tier conferences and journals, and clearly communicate research both internally and externally. - Stay at the forefront of foundational model and real-time multimodal AI research. What We’re Looking For - 5+ years of research experience in large-scale post-training of multimodal foundation models (LLMs, VLMs, Audio LMs, or similar), ideally at the staff or lead scientist level. - Track record as a first author on major publications in top conferences or journals (e.g., NeurIPS, ICML, ICLR). - Extensive hands-on experience with large-scale multimodal model design, training, and deployment. - Deep understanding and implementation experience with generative architectures (diffusion, autoregressive, cross-modal, etc.). - Expertise in high-throughput, scalable dataset curation and model pipeline optimization for multimodal applications. - Strong programming and prototyping skills (Python, PyTorch, TensorFlow, etc.) and experience deploying research into production systems. - Excellent communication and collaboration skills, and a passion for building creative enabling technology. What We Offer - Competitive salary and substantial equity in a high-growth startup - Full health benefits + 401k matching and more - Collaborative, mission-driven team environment with major growth opportunities - Flexible on-site/remote hybrid (HQ in Palo Alto, CA) About Pika Pika empowers creators by building state-of-the-art agentic and multimedia platforms. Our vision is to break down technical barriers to creativity, making real-time generative and intelligent orchestration accessible to all. Join us and help shape the next evolution of creative technology! If you are a leading researcher excited to build and scale real-time multimodal foundation models, we want to hear from you.

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