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Research Engineer, Multimodal

Character.AI - Redwood City, CA, Redwood City, California, United States

Posted Mar 6, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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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

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Engineering From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026

Schedule

Shift type
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Weekend work
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Company

Company stage
Growth-stage From the posting source checked Jun 20, 2026

Application

Cover letter
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Assessment
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Deadline
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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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