科技職缺
職缺列表
Data Platform Lead / Senior Data Engineer
Lead design and build of a next-gen financial data platform at LinqAlpha — large-scale structured and unstructured (PDF, multimodal) data pipelines, data warehouse/lake architecture, real-time and batch processing, hybrid on-prem + AWS/GCP infrastructure — using Python/Java, Kafka, Spark, and Airflow.
Frontend Engineer, AI Agent Product
Frontend engineer for an AI-native finance research agent B2B SaaS serving institutional investors. Builds streaming chat UIs, citation rendering, and generative UI outputs (documents, charts, spreadsheets, HTML) using React and TypeScript, with high-density financial interfaces.
[Live-Ops] 게임 UI/UX 디자이너 (3년 이상)
Design and produce mobile game UI/UX for live-operations titles at a top global mobile game publisher, collaborating with planners and developers to build intuitive layouts, system and monetization UI, and genre-flexible design solutions using tools like Photoshop, Illustrator, Figma, After Effects, and Unity.
Product Designer
Designs UX/UI across CatchTable's restaurant super-platform (consumer app and merchant solutions), leading product design end-to-end within a squad-based org. Collaborates with PM, engineers, and data analysts using Figma, Amplitude, A/B testing, and prototyping to drive measurable UX improvements.
Product UX/UI Designer (0-3년)
Lead UX/UI design for SeeAD's web/app product (70%) and growth/marketing visual design (30%) as an early member of a startup. Core tools are Figma and Adobe Photoshop/Illustrator, with mobile and web service design at the center.
AI Research Engineer
Research and develop on-device AI deep learning models for vehicle in-cabin sensing — designing computer vision models (detection, pose, segmentation), optimizing them for automotive SoCs, and leading experiments from problem definition through system integration. Core stack: Python, PyTorch, CNN/Transformer architectures.
ML Engineer - αprism
ML Engineer on Theori's αprism team developing NLP models for an AI security product that detects and blocks sensitive data leaks via generative-AI prompts. Day-to-day work: build and productionize NLP models, design ML serving infrastructure for SaaS/on-prem, run preprocessing/experiment/evaluation pipelines, and publish research.