How many AI roles reference Multimodal right now?

1,073 active AI roles across 126 companies in our index reference Multimodal as of today. New postings fell 30% in the last 30 days versus the prior 30 (473 → 332).

Which companies are hiring for Multimodal roles?

The companies with the most active Multimodal listings are: Amazon (227 roles), Google (104 roles), NVIDIA (80 roles), Adobe (77 roles), Apple (41 roles).

What AI lifecycle stage does Multimodal belong to?

Multimodal primarily belongs to the pre-training, post-training, and application stages of the AI lifecycle. In current hiring, Multimodal roles concentrate at: agents (34%), post-training (21%).

What sectors invest most in Multimodal?

The sectors with the most active Multimodal hiring are: Big Tech, Enterprise, Semiconductors.

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Multimodal

Models that process or generate across modalities — text, images, audio, video — within a single architecture; covers training, fine-tuning, and application-layer integration.

Primary AI lifecycle stage: pre-training, post-training, and application.

As of today, 1,073 active AI roles across 126 companies in our index reference Multimodal. Hiring concentrates at the agents (34%) and post-training (21%) stages. Most common sectors: Big Tech, Enterprise, Semiconductors. New postings fell 30% in the last 30 days versus the prior 30 (473 → 332).

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All Engineering · 1194 Research · 472 Product · 126

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35 AI roles tagged multimodal.

Company	Title	Sector	AI score	Other tags
Johnson & Johnson	Postdoctoral Data Analytics Computational Sciences	Pharma	9	Vision · Fine-tuning
Johnson & Johnson	Senior Scientist, AI Applications - R&D Immunology Data Science & Digital Health	Pharma	9	Agent orchestration · Agent research · LLM observability · Fine-tuning
Iambic	Machine Learning Scientist — Large multimodal models	Pharma	9	Fine-tuning · Inference infra · Model serving · Frontier research
Merck	Director, Data Science, Foundation Model AI	Pharma	9	Pretraining · Fine-tuning
Johnson & Johnson	Senior Scientist – AI Agent Systems for Drug Development	Pharma	9	Agent orchestration · Agent research · LLM observability · Interpretability
Johnson & Johnson	Sr Director/Scientific Fellow, AI Safety, R&D Data Science and Digital Health	Pharma	9	Agent orchestration · Guardrails · LLM observability · Evals · Frontier research · Agent research
Eli Lilly	Advisor - Applied Deep Learning Architect	Pharma	9
Johnson & Johnson	Senior Scientist, AI Applications - R&D Oncology	Pharma	9	Agent orchestration · Agent research · LLM observability · Interpretability
Iambic	Machine Learning Scientist – Clinical Prediction	Pharma	8	Fine-tuning · Evals · Model serving
Johnson & Johnson	Associate Director, R&D Neuroscience Data, Data Science & AI - Ophthalmology	Pharma	8
Johnson & Johnson	Director, R&D Neuroscience Data, Data Science & Artificial Intelligence - Ophthalmology	Pharma	8	Vision
Eli Lilly	Director, Discovery Bioinformatics Oncology	Pharma	8	Agent orchestration · Tool use · RAG · Fine-tuning
Johnson & Johnson	Associate Director, R&D Neuroscience Data, Data Science & AI – Ophthalmology	Pharma	8	Vision
Merck	Senior Data Scientist, Imaging Foundation Models	Pharma	8	Vision · Fine-tuning
Johnson & Johnson	Postdoctoral Researcher Video team	Pharma	8	Vision · Fine-tuning · Interpretability
Merck	Senior Scientist, Agentic AI and Machine Learning (PDMB)	Pharma	8	Agent orchestration · Tool use · LLM observability · Fine-tuning · RAG · Model serving
Merck	Senior Specialist, Data Science	Pharma	8	Agent orchestration · Tool use · Fine-tuning · LLM observability
Johnson & Johnson	Senior Machine Learning Engineer - Robotics	Pharma	8	Embodied AI · Model serving · Inference infra · Fine-tuning
Pfizer	Head, AI Delivery & Enablement (AIDE), Director	Pharma	8	Agent orchestration · Evals · Guardrails · LLM observability
Johnson & Johnson	Director, R&D Neuroscience Data Science & Digital Health – Ophthalmology	Pharma	8
Pfizer	AI/ML Engineer - Vaccine Research	Pharma	8	Fine-tuning
Pfizer	AI/ML Engineer - Vaccine Research	Pharma	8	Fine-tuning
Johnson & Johnson	Postdoctoral Researcher - AI in Digital Health	Pharma	8	Audio & speech · Fine-tuning
Johnson & Johnson	Senior Scientist, Computer Vision	Pharma	8	Vision · Model serving · Inference infra
Eli Lilly	Director, Discovery Bioinformatics Oncology	Pharma	8	Agent orchestration · Fine-tuning · RAG · Vector DB · Model serving
Iambic	Research Scientist II/Senior, Discovery ML	Pharma	8	Fine-tuning · Evals
Johnson & Johnson	Design Leader, Polyphonic AI Lab	Pharma	7	Model serving · Inference infra
Iambic	Research Scientist II/Senior, Discovery Machine Learning	Pharma	7	Fine-tuning · Evals
Merck	Senior Specialist, Image Data Analytics	Pharma	7
Johnson & Johnson	Sr Director, Head of Data Science & Digital Health – Preclinical Sciences & Translational Safety (PSTS)	Pharma	7	Agent orchestration

Frequently asked questions

What is Multimodal in AI?
Models that process or generate across modalities — text, images, audio, video — within a single architecture; covers training, fine-tuning, and application-layer integration. Primary AI lifecycle stage: pre-training, post-training, and application.
How many AI roles reference Multimodal right now?
1,073 active AI roles across 126 companies in our index reference Multimodal as of today. New postings fell 30% in the last 30 days versus the prior 30 (473 → 332).
Which companies are hiring for Multimodal roles?
The companies with the most active Multimodal listings are: Amazon (227 roles), Google (104 roles), NVIDIA (80 roles), Adobe (77 roles), Apple (41 roles).
What AI lifecycle stage does Multimodal belong to?
Multimodal primarily belongs to the pre-training, post-training, and application stages of the AI lifecycle. In current hiring, Multimodal roles concentrate at: agents (34%), post-training (21%).
What sectors invest most in Multimodal?
The sectors with the most active Multimodal hiring are: Big Tech, Enterprise, Semiconductors.