Job VC

We are looking for a
Senior AI/ML Engineer
experienced in
multimodal AI pipelines, LLM evaluation frameworks, agent orchestration, and scalable Python backend systems on AWS
.

A Korean company is building and hardening an
AI verification and compliance layer for AIGC/UGC financial content
.
The system includes:
four evaluation/verification models
an automated compliance rule engine
a Trust & Safety moderation pipeline
The core architecture processes
video-based content
through a multi-stage pipeline:
STT → OCR → image/video analysis → financial rules engine → LLM-based decision layer
Final output decision types:
Auto-Block
Auto-Pass
Human Review
This role requires strong production engineering skills combined with hands-on experience in
multimodal LLM evaluation systems
.

Required Skills & Experience
Multimodal LLM evaluation pipeline design
(LLM-as-a-judge, rubric-based scoring, prompt/few-shot optimization, schema design, agent orchestration)
Model evaluation engineering
(golden dataset creation, metric definition: precision/recall/human agreement, A/B testing, benchmarking automation)
AI serving & inference optimization
(AWS Bedrock integration, vLLM / GPU inference, latency optimization, cost-aware design, fallback strategies)
Strong Python backend engineering (~7–10 years)
(async systems, queues, microservices, service-oriented architecture)
Trust & Safety / compliance systems
(rule engines: keyword + context IF-THEN logic, moderation workflows, HITL queues, severity-based escalation)
Nice to Have
Experience fine-tuning or improving LLM / video understanding models
Background in content moderation or compliance systems
Experience with Korean language content processing
(STT, OCR optimization, NSFW detection pipelines)

Tech Stack
Languages / APIs:
Python (FastAPI), React (TypeScript)
LLM / Multimodal:
AWS Bedrock, VLMs (e.g. Qwen2.5-Omni), vLLM
Agent frameworks:
LangGraph, CrewAI, Google ADK, LangChain
Evaluation:
LLM-as-judge, rubric scoring, DeepEval-style eval harnesses
Cloud / Infra:
AWS Bedrock, SageMaker, RDS (PostgreSQL), S3, EKS
Observability:
Langfuse, prompt testing & tracing tools
Data platform:
Databricks
Media processing:
Whisper, OCR pipelines, image moderation tools (e.g. AWS Rekognition)