What is Recommendation Systems and how common is it in AI job postings?

Recommendation Systems is a skill in the "Applied ML Domains" category. It currently appears in 373 active AI roles across 69 companies in our index.

Which companies are hiring for Recommendation Systems?

The top employers with active AI roles mentioning Recommendation Systems are: Amazon (108), Google (31), JPMorgan Chase (18), Apple (18), Reddit (13).

Is demand for Recommendation Systems growing?

Over the last 12 weeks, 251 new AI postings mentioned Recommendation Systems. Demand is rising — up 314% in the last four weeks compared to the earliest four weeks in the window.

At which stage of AI development is Recommendation Systems used?

Roles requiring Recommendation Systems are concentrated in: application (49%), agents (33%), serving infrastructure (8%). These stages follow a seven-stage AI lifecycle from data preparation through to shipped product.

What skills are commonly paired with Recommendation Systems?

Job postings that mention Recommendation Systems most often also require: Machine Learning, Large Language Models (LLMs), Personalization, Ranking & Relevance, Natural Language Processing.

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Recommendation Systems

373 active AI roles across 69 companies mention Recommendation Systems. Category: Applied ML Domains.

Demand trend

New AI postings mentioning Recommendation Systems per week — 251 total over 12 weeks.

Sector

All Big Tech · 184 Consumer · 54 Enterprise · 35 Banking · 23 Retail · 15 Semiconductors · 14 Data AI · 12 AI Frontier · 10 Quant · 6 Media · 6 Hospitality · 4 Fintech · 4 Multimodal · 3 Telecom · 1 Pharma · 1 Healthcare · 1 Auto · 1

Function

All Engineering · 290 Research · 56 Product · 28

Status

All Active only

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FilteredsectorAI Frontier×

10 AI roles requiring this skill.

Company	Title	Sector	AI score	Stage
OpenAI	Research Engineer/Scientist - Human Alignment, Consumer Devices	AI Frontier	9	L2
Perplexity	Member of Technical Staff (Software Engineer, Applied AI)	AI Frontier	9	L4
OpenAI	Software Engineer, Accelerators	AI Frontier	9	L3
Perplexity	Member of Technical Staff (Machine Learning Engineer, Search)	AI Frontier	9	L4
Lila Sciences	AI Residency Program, Material Science (2026 Cohort)	AI Frontier	8	L1
OpenAI	Product Manager, Shopping	AI Frontier	7	L6
OpenAI	Applied Data Science & Insights Leader - GTM Intelligence Solutions and Technical Success	AI Frontier	7	L4
Perplexity	Member of Technical Staff (ML Engineer, Recommendations & User Modeling)	AI Frontier	7	L6
Character AI	Software Engineer, Applied ML (Discovery, Recommendation & Search)	AI Frontier	7	L6
xAI	Member of Technical Staff - Recommendation Systems	AI Frontier	7	L6

Frequently asked questions

What is Recommendation Systems and how common is it in AI job postings?
Recommendation Systems is a skill in the "Applied ML Domains" category. It currently appears in 373 active AI roles across 69 companies in our index.
Which companies are hiring for Recommendation Systems?
The top employers with active AI roles mentioning Recommendation Systems are: Amazon (108), Google (31), JPMorgan Chase (18), Apple (18), Reddit (13).
Is demand for Recommendation Systems growing?
Over the last 12 weeks, 251 new AI postings mentioned Recommendation Systems. Demand is rising — up 314% in the last four weeks compared to the earliest four weeks in the window.
At which stage of AI development is Recommendation Systems used?
Roles requiring Recommendation Systems are concentrated in: application (49%), agents (33%), serving infrastructure (8%). These stages follow a seven-stage AI lifecycle from data preparation through to shipped product.
What skills are commonly paired with Recommendation Systems?
Job postings that mention Recommendation Systems most often also require: Machine Learning, Large Language Models (LLMs), Personalization, Ranking & Relevance, Natural Language Processing.

Recommendation Systems

Top employers

Often paired with

Demand trend

Frequently asked questions

Recommendation Systems

Top employers

Often paired with

Demand trend

Frequently asked questions