Research Engineer, Multimodal
Character.AI - Redwood City, CA, Redwood City, California, United States
Posted Mar 6, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
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- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Market context
- Median wage (BLS OEWS)
- $111,944 national median
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
Matched to SOC 15-1252 - Data and ML aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Application
- Cover letter
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- Assessment
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- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Research Engineer, Multimodal Redwood City, CA, Redwood City, California, United States About the Role and Team Joining us as a Research Engineer on the Multimodal team, you'll be at the forefront of building and advancing video and image generation models that bring AI characters to life in entirely new ways. Your work will directly shape how millions of users experience rich, expressive, and visually compelling AI interactions every day. The Multimodal team is responsible for training, fine-tuning, and deploying cutting-edge image, audio and video generation models that power Character.AI 's visual experiences. We work across the full model lifecycle - from data pipelines and training to deployment and product integration. As a Multimodal Research Engineer, you will own and advance our video model training efforts, including joint audio-visual generation and image-to-video. You will collaborate across research, product, and infrastructure to push the boundaries of what AI-generated visuals can look and feel like at scale. What You'll Do - Lead fine-tuning and continued training of video generation models, including image-to-video and joint audio-visual generation. - Design and experiment with novel model architectures for multimodal generation, including multimodal conditioning (voice, structured text, reference images). - Leverage techniques such as LoRA, RLHF, and full-parameter fine-tuning to improve model quality across diverse visual scenarios. - Design and build large-scale data pipelines and automated annotation workflows to support continuous model improvement. - Explore model compression, inference acceleration, and serving optimizations to enable efficient real-time video processing at scale. Who You Are - Strong passion for
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