Multimodal AI Jobs (2026)
Multimodal AI combines multiple data types — text, images, video, audio — into unified systems that understand and generate across modalities. With models like GPT-4o, Gemini, and Claude becoming natively multimodal, demand for engineers who can build cross-modal AI systems is surging.
Last updated: June 27, 2026
Latest Multimodal AI Jobs
View all jobsMachine Learning Engineer – Computer Vision & Multimodal AI
AI Software Engineer (Multimodal AI Agents)
Applied Scientist - Multimodal Foundation Models & Robotics
AI Scientist - Biomedical Multimodal Modeling
[AI Research Div.] Research Engineer - Vision Language Action Game Agent (2년 이상 / 인턴)
Senior Machine Learning Engineer, Computer Vision/VLM
Senior Machine Learning Engineer, Multimodal AI
Senior Staff Machine Learning Engineer, LLM/VLM Model Architecture & Optimization
Portuguese Language Data Contributor (Multimodal) – Freelance AI Trainer Project
Data Scientist, Multimodal AI (AI Practice)
English Language Data Contributor (Multimodal) – Freelance AI Trainer Project
Spanish (Latin America) Language Data Contributor (Multimodal) – Freelance AI Trainer Project
Japanese Language Data Contributor (Multimodal) – Freelance AI Trainer Project
Korean Language Data Contributor (Multimodal) – Freelance AI Trainer Project
AI Research Scientist (Multimodal post-training)
Senior Applied Scientist - Multimodal
Staff Machine Learning Engineer - Computer Vision & Multi-Modal AI
Machine Learning Scientist, Multimodal AI
Staff Machine Learning Engineer – VLM/LLM Evaluation
Senior Machine Learning Engineer, Perception LLM/VLM
Frequently Asked Questions
What are multimodal AI systems?
Multimodal AI systems process and generate content across multiple modalities: text, images, video, audio, and code. Examples include vision-language models (GPT-4o, Gemini, Claude), text-to-image systems (DALL-E, Stable Diffusion), and audio-text models (Whisper). As AI engineer roles have surged 143% year-over-year, multimodal specialists are particularly sought after because building cross-modal systems requires a rare combination of CV and NLP expertise.
What skills do multimodal AI roles require?
Strong foundations in deep learning, transformer architectures, computer vision, and NLP are essential. Experience with cross-modal training, contrastive learning (CLIP), diffusion models, and multimodal evaluation is critical. PyTorch dominates as the primary framework, and Python appears in 47-58% of all AI listings. Cloud platform experience (AWS, GCP, Azure) is necessary for large-scale distributed training. Senior NLP roles at top tech companies can command up to $400K in total compensation.
What is the salary for multimodal AI engineers?
Multimodal AI engineers earn premium salaries due to the breadth of skills required. Computer vision specialists average around $169K, while NLP senior roles at top tech companies reach up to $400K. AI Engineers in this space average $140K-$185K base with total comp around $211K. US roles lead globally at $147K-$176K average, while Western Europe ranges from $72K-$160K. Workers with these specialized AI skills earn approximately 25% more than peers without AI expertise.
AI Job Insights for Multimodal AI Jobs
Salary Range (Yearly, USD)
$140K - $616K
Median $193K from 22 listings with salary data
Top Companies Hiring
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Common Roles
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In-Demand Skills
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