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AI Engineer
South Korea (Remote) • Full-time
- 원격
- 한국어: 비즈니스
- Machine Learning
- Python
- AI
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근무 형태: 원격
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ProCrewz® is a live-show crew workforce management SaaS platform built for event professionals across North America. Through its mobile app and client portal, the platform provides comprehensive HR capabilities including remote team collaboration, communication, time & attendance tracking, and payroll processing. The parent company, Program Productions Inc. (est. 1987), is a media company with deep industry connections, having worked with major U.S. broadcasters such as CBS and Fox.
Currently, a talent pool of approximately 25,000 event professionals operates through the platform, contributing to over 50,000 diverse events annually (NBA, MLB, UFC, concerts, conferences, and more).
Key Responsibilities
- Build and operate AI/automation solutions that serve all departments and functions
- Build a company-wide SSoT (Single Source of Truth) centralized dashboard / functional web applications
- Design and develop LLM-based RAG/Agent systems: retrieval, embedding, evaluation, and reasoning pipelines
- Develop Python-based AI backends: scalable services and APIs
Benefits of This Position
- Active AI initiatives: multiple projects across automation, data infrastructure, and intelligence — with a growing backlog driven by strong employee engagement
- AI tooling & token budget provided
- Direct collaboration with U.S.-based engineering and business teams
Qualifications
- 2+ years of relevant experience
- Business-level English proficiency
- Bachelor's degree or higher in Computer Science, Artificial Intelligence, Software Engineering, or equivalent experience
- System Design: ability to architect AI systems and solve complex technical problems
- ML/DL Proficiency: hands-on experience training and evaluating AI/ML models, with flexibility across languages and tooling.
- LLM Expertise: experience building and deploying LLM services or RAG/Agent systems
- Backend Development: experience developing REST API-based services (FastAPI, Flask, Django, etc.)
- Infrastructure Knowledge: experience deploying cloud-based services (GCP, Docker, Firestore, Python/TypeScript) in production. Comfortable extending or changing the stack as needs grow.
Preferred Qualifications
- Hands-on experience with AI serving optimization (vLLM, etc.) and monitoring GPU-based AI workloads
- DevOps/Infra: experience deploying and operating services on Docker/Kubernetes
- Data & Search: practical experience with databases and search systems such as PostgreSQL, Redis, Elasticsearch
- System Architecture: experience building cloud or on-premise AI infrastructure
Working Hours
- Minimum 4-hour overlap with U.S. Chicago Time Zone (CT)