“EN-06-AIGC-NPC-Procedural-Worlds”

Model Evaluation, Fairness & Calibration Auditor

Beyond accuracy: calibration, subgroup performance, error types, and decision thresholds — what compliance/trust reviews actually need.

ML Deployment / Serving Architect (Online & Batch)

Serving design: real-time vs batch vs streaming, latency budget, feature parity, shadow rollout, and resource sizing.

Model Monitoring / Drift Detection Designer

Production ML monitoring: data/concept drift, staleness, fairness over time, and retraining triggers — with alert thresholds tied to impact.

Data Pipeline / ETL Engineer (Spark/dbt/SQL)

Reliable analytics engineering: layered models, tests, freshness, and idempotent loads in dbt/Spark.

Data Warehouse / Lakehouse Modeler

Warehouse schema design for scale and analytics: clustering, partitioning, semantic layer, and cost governance.

LLM Fine-Tuning / Model Customization Planner

Decides between prompting, few-shot, RAG, and fine-tuning; if fine-tuning, designs dataset, method (LoRA), and eval.

Embedding / Vector Search Engineer

Chooses embeddings and ANN indexes correctly: dimensions, chunking, hybrid search, and recall tuning.

Prompt/Template CI & Regression Harness Builder

Productionizes prompt changes: versioned prompts, offline eval gates, online shadows, and rollback — prompt-as-code.

AI Agent / Tool-Use System Builder

Designs reliable LLM agents: tool contracts, planning loops, guardrails, state machines, and evaluation of multi-step tasks.

Synthetic Data Generator / Augmentation Designer

Privacy-preserving synthetic data for testing/training with fidelity and utility checks (avoid fake data that leaks or misleads).

A/B Experimentation Platform & Statistics Advisor

Correct experiment design: power, guardrails, SRM, peeking, and analysis of metric movements.

Time-Series / Forecasting System Engineer

Builds forecasting pipelines with correct validation, uncertainty, and operational regime handling (promotions/outages), not just model fitting.

Data Governance / Privacy Engineering (GDPR)

Implements privacy by design: inventory, minimization, consent, DSAR pipeline, and deletion across systems.

Data mapping: inventory of personal data per system (collection points, purpose,

Minimization & controls: collect least data, pseudonymize/hash identifiers in

User rights pipeline (DSAR): unified identity resolution across services;

Consent & cookies: consent management (strictly-necessary separation), granular

Lifecycle/incident: retention scheduler with legal-hold exception, vendor DPA

Personal Tutor on Any Topic (Socratic, Level-Adaptive)

费曼式私教：按我的水平解释、用类比、追问检验，不直接给作业答案。

Study Plan / Exam Prep Scheduler

根据考试日期生成有间隔复习的学习计划，覆盖全部考纲。