Information retrieval systems that order results by relevance, increasingly using neural rerankers and LLM-augmented post-processing on top of traditional inverted-index retrieval. Primary AI lifecycle stage: application.
490 active AI roles across 85 companies in our index reference Search & ranking as of today.
The companies with the most active Search & ranking listings are: Amazon (94 roles), Google (41 roles), Apple (26 roles), Reddit (18 roles), Pinterest (17 roles).
Search & ranking primarily belongs to the application stage of the AI lifecycle. In current hiring, Search & ranking roles concentrate at: application (46%), agents (42%).
The sectors with the most active Search & ranking hiring are: Big Tech, Consumer, Enterprise.
Information retrieval systems that order results by relevance, increasingly using neural rerankers and LLM-augmented post-processing on top of traditional inverted-index retrieval.
Primary AI lifecycle stage: application.
As of today, 490 active AI roles across 85 companies in our index reference Search & ranking. Hiring concentrates at the application (46%) and agents (42%) stages. Most common sectors: Big Tech, Consumer, Enterprise.
345 AI roles tagged search_ranking.
| Company | Title | Sector | AI score | Other tags |
|---|---|---|---|---|
| Senior Research Scientist, Google Research | Big Tech | 10 | Frontier research | |
| Amazon | Applied Scientist, EU INTech Consumer Selection Discovery, NintAI | Big Tech | 9 | Recommender systems · Model serving |
| Microsoft | Principal Applied Scientist | Big Tech | 9 | Agent orchestration · Tool use · Evals · Guardrails · LLM observability · RAG · Vector DB · Fine-tuning · Inference infra · Model serving · Recommender systems · Agent research |
| Apple | Engineering Manager, Maps Search Intelligence | Big Tech | 9 | LLM observability · Recommender systems |
| Meta | AI Research Scientist - Language - Meta AI (MRS) | Big Tech | 9 | Frontier research · Pretraining · LLM observability · Recommender systems |
| Apple | Machine Learning Engineer, Proactive | Big Tech | 9 | Fine-tuning · LLM observability · RAG · Recommender systems |
| Meta | Software Engineer, AI Specialist - Monetization (Technical Leadership) | Big Tech | 9 | Model serving · Inference infra · Recommender systems · Frontier research |
| Amazon | Principal Applied Scientist, Sponsored Products and Brands |
| Big Tech |
| 9 |
| Multimodal · Recommender systems · Model serving · Inference infra |
| Staff Research Scientist, Google Ads GenAI | Big Tech | 9 | Fine-tuning · RL post-training · LLM observability · Recommender systems |
| Meta | AI Research Scientist, CoreML - Monetization AI | Big Tech | 9 | Pretraining · Fine-tuning · RL post-training · Recommender systems · Quantization |
| Apple | Principal Applied Researcher | Big Tech | 9 | Agent orchestration · RAG · Fine-tuning · Evals · Frontier research · LLM observability · Multimodal · Recommender systems · RL post-training · Guardrails |
| Meta | AI Research Scientist, CoreML - Monetization | Big Tech | 9 | Recommender systems · Fine-tuning · Pretraining |
| Amazon | Sr. Applied Science Manager, Perfect Order Experience (POE) AI | Big Tech | 9 | Pretraining · Fine-tuning · RL post-training · Multimodal · Model serving |
| Meta | Research Engineer, Monetization AI | Big Tech | 9 | Fine-tuning · Frontier research · RL post-training · LLM observability |
| Meta | AI Research Scientist, CoreML - Monetization AI | Big Tech | 9 | Frontier research · Pretraining · Fine-tuning · RL post-training · Recommender systems |
| Netflix | Research Scientist 5/6 – AI for Member Systems | Big Tech | 9 | Fine-tuning · Recommender systems · Frontier research |
| Amazon | Senior Applied Scientist, Sponsored Products and Brands | Big Tech | 8 | Fine-tuning · Recommender systems · RAG · RLHF |
| Apple | Machine Learning Manager - AI, Search & Knowledge Platforms | Big Tech | 8 | Agent orchestration · LLM observability · RAG · Model serving · Agent research |
| Amazon | Data Scientist II, RufusX Science UK | Big Tech | 8 | Agent orchestration · Multimodal · Recommender systems · RAG · Inference infra · Model serving |
| Microsoft | Principal Applied Scientist | Big Tech | 8 | Frontier research |
| Amazon | Applied Scientist, EU INTech Consumer Selection Discovery, NintAI | Big Tech | 8 | Recommender systems |
| Staff Software Engineer, Knowledge Catalog, AI | Big Tech | 8 | Agent orchestration · Model serving · Inference infra · Multimodal · Vision · Recommender systems · LLM observability |
| Product Manager, Workspace Search | Big Tech | 8 | Agent orchestration · Tool use · Evals · RAG |
| Microsoft | Applied Science: PhD Microsoft AI Internship Opportunities - Redmond | Big Tech | 8 | Recommender systems · Model serving · Inference infra |
| Apple | Machine Learning Engineer, ASE Search Team | Big Tech | 8 | Recommender systems · LLM observability · RAG · Vector DB · Fine-tuning · Model serving |
| Netflix | ML Software Engineer 6 - AI for Member Systems (AIMS) | Big Tech | 8 | Model serving · Inference infra · Recommender systems · Agent orchestration |
| Apple | Staff Machine Learning Engineer – Ads Signals Intelligence & Information Retrieval | Big Tech | 8 | Recommender systems · Fine-tuning · Multimodal · LLM observability · RAG · Vector DB |
| Microsoft | Senior Applied Scientist | Big Tech | 8 | Recommender systems · LLM observability · Model serving · Inference infra · Fine-tuning |
| Senior Software Engineering Manager, AI/ML Recommendations, Rankings, Predictions, YouTube | Big Tech | 8 | Recommender systems · Model serving · Inference infra |
| Research Engineer, Ads AI | Big Tech | 8 | RL post-training · Agent orchestration · Multimodal · Recommender systems |