Showing 187 tagged AI roles in Media. Layout is a Fruchterman-Reingold force simulation, run server-side to convergence.
agent_orchestration ↔ agent_research (12 JDs) agent_orchestration ↔ multimodal (5 JDs) agent_orchestration ↔ rag (34 JDs) agent_orchestration ↔ llm_observability (61 JDs) agent_orchestration ↔ evals (28 JDs) agent_orchestration ↔ guardrails (35 JDs) agent_orchestration ↔ model_serving (40 JDs) agent_orchestration ↔ inference_infra (16 JDs) agent_research ↔ multimodal (1 JDs) agent_research ↔ rag (7 JDs) agent_research ↔ llm_observability (11 JDs) agent_research ↔ evals (9 JDs) agent_research ↔ guardrails (5 JDs) agent_research ↔ model_serving (4 JDs) agent_research ↔ inference_infra (3 JDs) multimodal ↔ rag (6 JDs) llm_observability ↔ multimodal (3 JDs) evals ↔ multimodal (7 JDs) guardrails ↔ multimodal (1 JDs) model_serving ↔ multimodal (9 JDs) inference_infra ↔ multimodal (3 JDs) llm_observability ↔ rag (31 JDs) evals ↔ rag (16 JDs) guardrails ↔ rag (13 JDs) model_serving ↔ rag (22 JDs) inference_infra ↔ rag (14 JDs) evals ↔ llm_observability (34 JDs) guardrails ↔ llm_observability (31 JDs) llm_observability ↔ model_serving (41 JDs) inference_infra ↔ llm_observability (20 JDs) evals ↔ guardrails (18 JDs) evals ↔ model_serving (23 JDs) evals ↔ inference_infra (9 JDs) guardrails ↔ model_serving (17 JDs) guardrails ↔ inference_infra (8 JDs) inference_infra ↔ model_serving (42 JDs) agent_orchestration ↔ fine_tuning (17 JDs) fine_tuning ↔ llm_observability (15 JDs) fine_tuning ↔ model_serving (29 JDs) evals ↔ fine_tuning (15 JDs) fine_tuning ↔ guardrails (7 JDs) agent_research ↔ fine_tuning (4 JDs) agent_orchestration ↔ tool_use (29 JDs) agent_research ↔ tool_use (7 JDs) llm_observability ↔ tool_use (23 JDs) rag ↔ tool_use (14 JDs) model_serving ↔ tool_use (13 JDs) inference_infra ↔ tool_use (5 JDs) evals ↔ tool_use (8 JDs) fine_tuning ↔ tool_use (7 JDs) fine_tuning ↔ rl_post_training (2 JDs) fine_tuning ↔ synthetic_data (2 JDs) evals ↔ rl_post_training (2 JDs) rl_post_training ↔ synthetic_data (2 JDs) agent_research ↔ rl_post_training (2 JDs) evals ↔ synthetic_data (2 JDs) agent_research ↔ synthetic_data (2 JDs) agent_orchestration ↔ code_gen (1 JDs) code_gen ↔ tool_use (1 JDs) code_gen ↔ evals (1 JDs) code_gen ↔ llm_observability (1 JDs) agent_research ↔ code_gen (1 JDs) agent_orchestration ↔ vector_db (16 JDs) rag ↔ vector_db (25 JDs) fine_tuning ↔ rag (12 JDs) fine_tuning ↔ vector_db (10 JDs) model_serving ↔ vector_db (12 JDs) llm_observability ↔ vector_db (14 JDs) evals ↔ vector_db (7 JDs) guardrails ↔ tool_use (8 JDs) tool_use ↔ vector_db (4 JDs) guardrails ↔ vector_db (7 JDs) agent_research ↔ vector_db (3 JDs) forecasting ↔ model_serving (5 JDs) forecasting ↔ inference_infra (2 JDs) forecasting ↔ llm_observability (2 JDs) agent_orchestration ↔ vision (3 JDs) agent_orchestration ↔ audio_speech (4 JDs) multimodal ↔ tool_use (1 JDs) tool_use ↔ vision (2 JDs) audio_speech ↔ tool_use (2 JDs) rag ↔ vision (5 JDs) audio_speech ↔ rag (2 JDs) multimodal ↔ vector_db (4 JDs) vector_db ↔ vision (4 JDs) audio_speech ↔ vector_db (2 JDs) fine_tuning ↔ multimodal (9 JDs) fine_tuning ↔ vision (6 JDs) audio_speech ↔ fine_tuning (5 JDs) model_serving ↔ vision (9 JDs) audio_speech ↔ model_serving (5 JDs) multimodal ↔ vision (7 JDs) audio_speech ↔ multimodal (4 JDs) audio_speech ↔ vision (2 JDs) recommender_systems ↔ search_ranking (14 JDs) fine_tuning ↔ recommender_systems (5 JDs) rag ↔ recommender_systems (4 JDs) llm_observability ↔ recommender_systems (6 JDs) multimodal ↔ recommender_systems (3 JDs) recommender_systems ↔ vision (4 JDs) evals ↔ recommender_systems (3 JDs) fine_tuning ↔ search_ranking (4 JDs) rag ↔ search_ranking (4 JDs) llm_observability ↔ search_ranking (6 JDs) multimodal ↔ search_ranking (1 JDs) search_ranking ↔ vision (2 JDs) evals ↔ search_ranking (3 JDs) llm_observability ↔ vision (5 JDs) evals ↔ vision (5 JDs) inference_infra ↔ vision (5 JDs) model_serving ↔ recommender_systems (17 JDs) model_serving ↔ search_ranking (9 JDs) inference_infra ↔ recommender_systems (9 JDs) inference_infra ↔ search_ranking (6 JDs) fine_tuning ↔ inference_infra (9 JDs) inference_infra ↔ vector_db (7 JDs) agent_orchestration ↔ recommender_systems (4 JDs) agent_orchestration ↔ search_ranking (3 JDs) agent_orchestration ↔ frontier_research (1 JDs) agent_orchestration ↔ interpretability (1 JDs) agent_orchestration ↔ synthetic_data (1 JDs) agent_orchestration ↔ rl_post_training (1 JDs) agent_orchestration ↔ rlhf (1 JDs) agent_orchestration ↔ reward_modeling (1 JDs) agent_orchestration ↔ rl_robotics (1 JDs) agent_orchestration ↔ embodied_ai (1 JDs) recommender_systems ↔ tool_use (2 JDs) search_ranking ↔ tool_use (2 JDs) frontier_research ↔ tool_use (1 JDs) interpretability ↔ tool_use (1 JDs) synthetic_data ↔ tool_use (1 JDs) rl_post_training ↔ tool_use (1 JDs) rlhf ↔ tool_use (1 JDs) reward_modeling ↔ tool_use (1 JDs) rl_robotics ↔ tool_use (1 JDs) embodied_ai ↔ tool_use (1 JDs) audio_speech ↔ evals (2 JDs) evals ↔ frontier_research (1 JDs) evals ↔ interpretability (1 JDs) evals ↔ rlhf (1 JDs) evals ↔ reward_modeling (1 JDs) evals ↔ rl_robotics (1 JDs) embodied_ai ↔ evals (1 JDs) guardrails ↔ recommender_systems (3 JDs) guardrails ↔ search_ranking (3 JDs) guardrails ↔ vision (1 JDs) audio_speech ↔ guardrails (1 JDs) frontier_research ↔ guardrails (1 JDs) guardrails ↔ interpretability (1 JDs) guardrails ↔ synthetic_data (1 JDs) guardrails ↔ rl_post_training (1 JDs) guardrails ↔ rlhf (1 JDs) guardrails ↔ reward_modeling (1 JDs) guardrails ↔ rl_robotics (1 JDs) embodied_ai ↔ guardrails (1 JDs) audio_speech ↔ llm_observability (1 JDs) frontier_research ↔ llm_observability (1 JDs) interpretability ↔ llm_observability (1 JDs) llm_observability ↔ synthetic_data (1 JDs) llm_observability ↔ rl_post_training (1 JDs) llm_observability ↔ rlhf (1 JDs) llm_observability ↔ reward_modeling (1 JDs) llm_observability ↔ rl_robotics (1 JDs) embodied_ai ↔ llm_observability (1 JDs) frontier_research ↔ rag (1 JDs) interpretability ↔ rag (1 JDs) rag ↔ synthetic_data (1 JDs) rag ↔ rl_post_training (1 JDs) rag ↔ rlhf (1 JDs) rag ↔ reward_modeling (1 JDs) rag ↔ rl_robotics (1 JDs) embodied_ai ↔ rag (1 JDs) recommender_systems ↔ vector_db (2 JDs) search_ranking ↔ vector_db (3 JDs) frontier_research ↔ vector_db (1 JDs) interpretability ↔ vector_db (1 JDs) synthetic_data ↔ vector_db (1 JDs) rl_post_training ↔ vector_db (1 JDs) rlhf ↔ vector_db (1 JDs) reward_modeling ↔ vector_db (1 JDs) rl_robotics ↔ vector_db (1 JDs) embodied_ai ↔ vector_db (1 JDs) fine_tuning ↔ frontier_research (1 JDs) fine_tuning ↔ interpretability (1 JDs) fine_tuning ↔ rlhf (1 JDs) fine_tuning ↔ reward_modeling (1 JDs) fine_tuning ↔ rl_robotics (1 JDs) embodied_ai ↔ fine_tuning (1 JDs) audio_speech ↔ inference_infra (1 JDs) frontier_research ↔ inference_infra (1 JDs) inference_infra ↔ interpretability (1 JDs) inference_infra ↔ synthetic_data (1 JDs) inference_infra ↔ rl_post_training (1 JDs) inference_infra ↔ rlhf (1 JDs) inference_infra ↔ reward_modeling (1 JDs) inference_infra ↔ rl_robotics (1 JDs) embodied_ai ↔ inference_infra (1 JDs) frontier_research ↔ model_serving (1 JDs) interpretability ↔ model_serving (1 JDs) model_serving ↔ synthetic_data (1 JDs) model_serving ↔ rl_post_training (1 JDs) model_serving ↔ rlhf (1 JDs) model_serving ↔ reward_modeling (1 JDs) model_serving ↔ rl_robotics (1 JDs) embodied_ai ↔ model_serving (1 JDs) audio_speech ↔ recommender_systems (1 JDs) frontier_research ↔ recommender_systems (2 JDs) interpretability ↔ recommender_systems (1 JDs) recommender_systems ↔ synthetic_data (1 JDs) agent_research ↔ recommender_systems (2 JDs) recommender_systems ↔ rl_post_training (1 JDs) recommender_systems ↔ rlhf (1 JDs) recommender_systems ↔ reward_modeling (1 JDs) recommender_systems ↔ rl_robotics (1 JDs) embodied_ai ↔ recommender_systems (1 JDs) audio_speech ↔ search_ranking (1 JDs) frontier_research ↔ search_ranking (1 JDs) interpretability ↔ search_ranking (1 JDs) search_ranking ↔ synthetic_data (1 JDs) agent_research ↔ search_ranking (2 JDs) rl_post_training ↔ search_ranking (1 JDs) rlhf ↔ search_ranking (1 JDs) reward_modeling ↔ search_ranking (1 JDs) rl_robotics ↔ search_ranking (1 JDs) embodied_ai ↔ search_ranking (1 JDs) frontier_research ↔ vision (1 JDs) interpretability ↔ vision (1 JDs) synthetic_data ↔ vision (1 JDs) agent_research ↔ vision (1 JDs) rl_post_training ↔ vision (1 JDs) rlhf ↔ vision (1 JDs) reward_modeling ↔ vision (1 JDs) rl_robotics ↔ vision (1 JDs) embodied_ai ↔ vision (1 JDs) audio_speech ↔ frontier_research (1 JDs) audio_speech ↔ interpretability (1 JDs) audio_speech ↔ synthetic_data (2 JDs) agent_research ↔ audio_speech (1 JDs) audio_speech ↔ rl_post_training (1 JDs) audio_speech ↔ rlhf (1 JDs) audio_speech ↔ reward_modeling (1 JDs) audio_speech ↔ rl_robotics (1 JDs) audio_speech ↔ embodied_ai (1 JDs) frontier_research ↔ interpretability (1 JDs) frontier_research ↔ synthetic_data (1 JDs) agent_research ↔ frontier_research (1 JDs) frontier_research ↔ rl_post_training (1 JDs) frontier_research ↔ rlhf (1 JDs) frontier_research ↔ reward_modeling (1 JDs) frontier_research ↔ rl_robotics (1 JDs) embodied_ai ↔ frontier_research (1 JDs) interpretability ↔ synthetic_data (1 JDs) agent_research ↔ interpretability (1 JDs) interpretability ↔ rl_post_training (1 JDs) interpretability ↔ rlhf (1 JDs) interpretability ↔ reward_modeling (1 JDs) interpretability ↔ rl_robotics (1 JDs) embodied_ai ↔ interpretability (1 JDs) rlhf ↔ synthetic_data (1 JDs) reward_modeling ↔ synthetic_data (1 JDs) rl_robotics ↔ synthetic_data (1 JDs) embodied_ai ↔ synthetic_data (1 JDs) agent_research ↔ rlhf (1 JDs) agent_research ↔ reward_modeling (1 JDs) agent_research ↔ rl_robotics (1 JDs) agent_research ↔ embodied_ai (1 JDs) rl_post_training ↔ rlhf (1 JDs) reward_modeling ↔ rl_post_training (1 JDs) rl_post_training ↔ rl_robotics (1 JDs) embodied_ai ↔ rl_post_training (1 JDs) reward_modeling ↔ rlhf (1 JDs) rl_robotics ↔ rlhf (1 JDs) embodied_ai ↔ rlhf (1 JDs) reward_modeling ↔ rl_robotics (1 JDs) embodied_ai ↔ reward_modeling (1 JDs) embodied_ai ↔ rl_robotics (1 JDs) forecasting ↔ recommender_systems (2 JDs) forecasting ↔ multimodal (1 JDs) Agent orchestration
N=95 JDs
Top co-occur: LLM observability ×61 · Model serving ×40 · Guardrails ×35 Agent orchestration Agent research
N=13 JDs
Top co-occur: Agent orchestration ×12 · LLM observability ×11 · Evals ×9 Multimodal
N=15 JDs
Top co-occur: Model serving ×9 · Fine-tuning ×9 · Evals ×7 RAG
N=46 JDs
Top co-occur: Agent orchestration ×34 · LLM observability ×31 · Vector DB ×25 RAG LLM observability
N=82 JDs
Top co-occur: Agent orchestration ×61 · Model serving ×41 · Evals ×34 LLM observability Evals
N=42 JDs
Top co-occur: LLM observability ×34 · Agent orchestration ×28 · Model serving ×23 Evals Guardrails
N=39 JDs
Top co-occur: Agent orchestration ×35 · LLM observability ×31 · Evals ×18 Guardrails Model serving
N=96 JDs
Top co-occur: Inference infra ×42 · LLM observability ×41 · Agent orchestration ×40 Model serving Inference infra
N=43 JDs
Top co-occur: Model serving ×42 · LLM observability ×20 · Agent orchestration ×16 Inference infra Fine-tuning
N=33 JDs
Top co-occur: Model serving ×29 · Agent orchestration ×17 · LLM observability ×15 Fine-tuning Tool use
N=29 JDs
Top co-occur: Agent orchestration ×29 · LLM observability ×23 · RAG ×14 Tool use RL post-training
N=2 JDs
Top co-occur: Fine-tuning ×2 · Evals ×2 · Synthetic data ×2 Synthetic data
N=3 JDs
Top co-occur: Fine-tuning ×2 · RL post-training ×2 · Evals ×2 Forecasting
N=11 JDs
Top co-occur: Model serving ×5 · Inference infra ×2 · LLM observability ×2 Code gen
N=1 JDs
Top co-occur: Agent orchestration ×1 · Tool use ×1 · Evals ×1 Vector DB
N=25 JDs
Top co-occur: RAG ×25 · Agent orchestration ×16 · LLM observability ×14 Vector DB Vision
N=16 JDs
Top co-occur: Model serving ×9 · Multimodal ×7 · Fine-tuning ×6 Audio & speech
N=6 JDs
Top co-occur: Fine-tuning ×5 · Model serving ×5 · Agent orchestration ×4 Recommender systems
N=33 JDs
Top co-occur: Model serving ×17 · Search & ranking ×14 · Inference infra ×9 Recommender systems Search & ranking
N=15 JDs
Top co-occur: Recommender systems ×14 · Model serving ×9 · LLM observability ×6 Data pipeline
N=1 JDs Frontier research
N=2 JDs
Top co-occur: Recommender systems ×2 · Agent orchestration ×1 · Tool use ×1 Interpretability
N=1 JDs
Top co-occur: Agent orchestration ×1 · Tool use ×1 · Evals ×1 RLHF
N=1 JDs
Top co-occur: Agent orchestration ×1 · Tool use ×1 · Evals ×1 Reward modeling
N=1 JDs
Top co-occur: Agent orchestration ×1 · Tool use ×1 · Evals ×1 RL robotics
N=1 JDs
Top co-occur: Agent orchestration ×1 · Tool use ×1 · Evals ×1 Embodied AI
N=1 JDs
Top co-occur: Agent orchestration ×1 · Tool use ×1 · Evals ×1 27 tags · 278 co-occurrence edges · min edge weight 1. Bubble area ∝ JDs containing tag · edge thickness ∝ co-occurrence count. Hover any node for top-3 partners; click to see the JDs. Tag velocity · last 4 weeks vs prior 4 Which technologies are hot, which are cooling. Sparkline = 12 weeks of unique roles tagged with each term, last bar on the right is this week. Sorted by absolute pickup. Tags with under 10 lifetime mentions are hidden as noise.