Adapting a pretrained model to specific data or behavior through additional training, including supervised fine-tuning, preference tuning (DPO, ORPO), and LoRA-style parameter-efficient methods. Primary AI lifecycle stage: post-training.
1,893 active AI roles across 204 companies in our index reference Fine-tuning as of today. New postings fell 23% in the last 30 days versus the prior 30 (830 → 636).
The companies with the most active Fine-tuning listings are: Amazon (235 roles), Capital One (127 roles), Google (98 roles), JPMorgan Chase (86 roles), NVIDIA (77 roles).
Fine-tuning primarily belongs to the post-training stage of the AI lifecycle. In current hiring, Fine-tuning roles concentrate at: agents (44%), post-training (26%).
The sectors with the most active Fine-tuning hiring are: Big Tech, Enterprise, Banking.
Adapting a pretrained model to specific data or behavior through additional training, including supervised fine-tuning, preference tuning (DPO, ORPO), and LoRA-style parameter-efficient methods.
Primary AI lifecycle stage: post-training.
As of today, 1,893 active AI roles across 204 companies in our index reference Fine-tuning. Hiring concentrates at the agents (44%) and post-training (26%) stages. Most common sectors: Big Tech, Enterprise, Banking. New postings fell 23% in the last 30 days versus the prior 30 (830 → 636).
22 AI roles tagged fine_tuning.
| Company | Title | Sector | AI score | Other tags |
|---|---|---|---|---|
| Verizon | Princ Engr-AI Science | Telecom | 9 | Agent orchestration · Multi-agent · Tool use · RAG · Vector DB · LLM observability |
| AT&T | Director Cybersecurity - AI/ML/Automation (Cyber Threat Analytics) | Telecom | 8 | Agent orchestration · Tool use · Evals · Guardrails · LLM observability · Inference infra · Model serving |
| Verizon | Engr III Cslt-AI Science | Telecom | 8 | Agent orchestration · RAG · Vector DB · Model serving · Inference infra · LLM observability |
| Verizon | Princ Engr-AI Science | Telecom | 8 | Agent orchestration · RAG · Vector DB · Model serving · Inference infra · LLM observability · Multimodal |
| Verizon | Sr Engr Cslt-Data Science | Telecom | 8 | Agent orchestration · Tool use · RAG · LLM observability · Model serving |
| T-Mobile | Sr AI Engineer | Telecom | 8 | Agent orchestration · Tool use · RAG · Agent research · LLM observability |
| Verizon | Senior Data Scientist | Telecom | 8 | Agent orchestration · RAG · Vector DB · Model serving |
| Verizon | Principal Data Scientist | Telecom | 8 | Agent orchestration · LLM observability · RAG · Model serving · Recommender systems · Search & ranking |
| Verizon | Sr Engr Cslt-AI Science | Telecom | 8 | Agent orchestration · Agent research · Inference infra · Model serving · LLM observability · RAG |
| T-Mobile | Sr Engineer, Machine Learning Engineering | Telecom | 8 | Agent orchestration · RAG · Model serving · LLM observability · Multimodal · Evals |
| T-Mobile | Sr. AI Engineer | Telecom | 8 | Agent orchestration · Tool use · RAG · LLM observability · Evals · Guardrails |
| T-Mobile | Associate AI Engineer | Telecom | 7 | Agent orchestration · RAG · Tool use · LLM observability |
| T-Mobile | Sr Data Scientist | Telecom | 7 | Model serving |
| Verizon | Engineer Full Stack - AI | Telecom | 7 | Agent orchestration · RAG · LLM observability |
| Verizon | Data and AI Engineer | Telecom | 7 | RAG · LLM observability |
| Verizon | Director of Digital Customer Experience & AI Innovation | Telecom | 7 | LLM observability · Agent orchestration · Guardrails · RAG · Vector DB · Model serving · Recommender systems · Search & ranking · Interpretability · Synthetic data · Agent research · RL post-training · RLHF · Reward modeling · RL robotics · Embodied AI |
| Verizon | Spec-Product Dev/Mgt | Telecom | 7 | Agent orchestration · RAG · Evals · LLM observability · Guardrails |
| Verizon | AI Product Manager | Telecom | 7 | Agent orchestration · RAG · Guardrails · LLM observability · Model serving |
| AT&T | Sr Specialist Quality/M&P/Process - AI Training Manager | Telecom | 7 | Agent orchestration · Evals · Guardrails · LLM observability |
| AT&T | Senior Full Stack/AI Engineer | Telecom | 5 | LLM observability · Agent orchestration · RAG · Vector DB · Model serving · Recommender systems · 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 |
| AT&T | Lead Applications Development | Telecom | 5 | Agent orchestration · Tool use · LLM observability · RAG · Model serving |
| AT&T | Full-Stack Software Engineer | Telecom | 5 | Agent orchestration · Tool use · LLM observability · RAG · Vector DB · Model serving · Recommender systems · 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 |