Personalized ranking systems that predict which items a user will engage with — historically classical ML, increasingly LLM-augmented with semantic reranking and conversational interfaces.
Primary AI lifecycle stage: application.
As of today, 844 active AI roles across 98 companies in our index reference Recommender systems. Hiring concentrates at the application (49%) and agents (35%) stages. Most common sectors: Big Tech, Consumer, Enterprise.
Personalized ranking systems that predict which items a user will engage with — historically classical ML, increasingly LLM-augmented with semantic reranking and conversational interfaces. Primary AI lifecycle stage: application.
844 active AI roles across 98 companies in our index reference Recommender systems as of today.
The companies with the most active Recommender systems listings are: Amazon (221 roles), Google (52 roles), Walmart (49 roles), Apple (33 roles), JPMorgan Chase (28 roles).
Recommender systems primarily belongs to the application stage of the AI lifecycle. In current hiring, Recommender systems roles concentrate at: application (49%), agents (35%).
The sectors with the most active Recommender systems hiring are: Big Tech, Consumer, Enterprise.
7 AI roles tagged recommender_systems.
| Company | Title | Sector | AI score | Other tags |
|---|---|---|---|---|
| Verizon | Principal Data Scientist | Telecom | 8 | Agent orchestration · LLM observability · RAG · Fine-tuning · Model serving · Search & ranking |
| Verizon | Engr III Cslt-Data Science | Telecom | 7 | |
| Verizon | Director of Digital Customer Experience & AI Innovation | Telecom | 7 | LLM observability · Agent orchestration · Guardrails · RAG · Vector DB · Fine-tuning · Model serving · Search & ranking · Interpretability · Synthetic data · Agent research · RL post-training · RLHF · Reward modeling · RL robotics · Embodied AI |
| AT&T | Director of Engineering – Decision Intelligence Platform | Telecom | 7 | Model serving · Inference infra · LLM observability · Search & ranking |
| AT&T | Senior Full Stack/AI Engineer | Telecom | 5 | LLM observability · Agent orchestration · RAG · Vector DB · Fine-tuning · Model serving · Search & ranking · Vision · Multimodal · Audio & speech · Frontier research · Interpretability · Synthetic data · Agent research · RL post-training · RLHF · Reward modeling · RL robotics · Embodied AI · Code gen |
| T-Mobile | Software Engineer- Android | Telecom | 5 | |
| AT&T | Full-Stack Software Engineer | Telecom | 5 | Agent orchestration · Tool use · LLM observability · RAG · Vector DB · Fine-tuning · Model serving · Search & ranking · Vision · Multimodal · Audio & speech · Frontier research · Interpretability · Synthetic data · Agent research · RL post-training · RLHF · Reward modeling · RL robotics · Embodied AI · Code gen |