Research Scientist, Foundation Model
Palo Alto HQ • FullTime
Posted 2mo ago
Remote Work Policy
On-site
Employment Type
FullTime
Categories
AI Research Engineer
About the job
Pika is pioneering the next generation of creative infrastructure with real-time, multimodal generation and intelligent agentic platforms. We are seeking accomplished Research Scientists in Foundation Models to advance our mission of making agentic, real-time generative technology accessible and transformative for millions of creators. As a key member of our research team, you will design and implement core technologies, develop new methodologies for large-scale multimodal pre-training/mid-training, and drive innovative approaches for foundational model architecture, collaborating closely with engineering and product teams to shape the future of real-time creative and agentic platforms at scale.
Responsibilities
- Lead research and development on pre-training and mid-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 pre-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.
Requirements
- 5+ years of research experience in large-scale pre-training/mid-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.
Benefits
- 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