multimodal models jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-28, multimodal models appears in 243 job postings indexed by Skillenai over the past 90 days — Machine Learning Engineer has the most postings mentioning multimodal models, with demand up 15% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-28

Postings · last 90 days
243
Demand vs prior month
up 15% vs the prior 4 weeks
Top role · 11.9% of skill postings
Top hiring metro
San Francisco

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Frequently asked questions about multimodal models

+Is multimodal models in demand in 2026?

Yes. multimodal models appears in 243 job postings indexed by Skillenai over the 90 days ending 2026-09-28, with demand up 15% vs the prior 4 weeks. Machine Learning Engineer accounts for the most postings mentioning multimodal models (11.9% of all postings mentioning multimodal models).

+What jobs require multimodal models?

According to the Skillenai jobs index over the 90 days ending 2026-09-28, among roles with at least 20 postings, the highest shares mentioning multimodal models are Applied Machine Learning Engineer (25.0% of that role’s postings mention multimodal models), Agent Architect (14.3% of that role’s postings mention multimodal models), Deep Learning Engineer (12.1% of that role’s postings mention multimodal models).

+What skills are commonly paired with multimodal models?

Across job postings indexed by Skillenai (90 days ending 2026-09-28), multimodal models most often appears alongside Python, PyTorch, fine-tuning, LLMs, machine learning.

+Where is multimodal models most in demand?

As of 2026-09-28, the metro areas posting the most jobs requiring multimodal models are San Francisco, Sunnyvale, San Mateo, London, Singapore, according to the Skillenai jobs index.

+How can I keep up with new multimodal models content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning multimodal models alongside the jobs index. You can subscribe to a daily email digest of new multimodal models content from your Skillenai account.

Weekly job postings requiring multimodal models — last 90 days

Salary distribution

Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized

Roles most likely to require multimodal models

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Applied Machine Learning Engineer625.0%
Agent Architect514.3%
Deep Learning Engineer412.1%
Machine Learning Researcher25.1%
Gen AI Engineer15.0%
Applied Researcher24.8%
Agent Engineer14.8%
Applied ML Engineer14.8%
AI Research Intern14.5%
Postdoctoral Researcher14.5%

Roles with the most multimodal models postings

RolePostings mentioning skillShare of skill postings
Machine Learning Engineer2911.9%
Research Scientist135.3%
Software Engineer124.9%
Product Manager114.5%
AI Engineer104.1%
ML Engineer104.1%
AI Field Engineer93.7%
AI Software Engineer83.3%
Applied Machine Learning Engineer62.5%
Engineering Manager62.5%

Top metros hiring for multimodal models

NamePostingsShare
San Francisco249.9%
Sunnyvale249.9%
San Mateo135.3%
London124.9%
Singapore124.9%
Mountain View93.7%
Bengaluru83.3%
New York City83.3%
Amsterdam62.5%

Skills commonly paired with multimodal models

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How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-28. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning multimodal models by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s multimodal models postings by all multimodal models postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills).

source
Skillenai jobs index, deduplicated daily
entity_id
2e86d8b9c0da3bc7
data_as_of
2026-09-28
window_days
90
Hiring engineers who use multimodal models?

The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.

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Compiled by Jared Rand · Data sourced from the Skillenai labor market index