Data Engineer/ Data Scientist

7 hours ago

Taipei Taipei City, Taiwan Robert Walters Full time NT$1,200,000 - NT$3,600,000 per year

I am working with a leading large-scale tech company to hire a Senior Data Engineer / AI Platform Engineer who will shape their next-generation data and AI infrastructure, supporting high-traffic products and search/recommendation systems. We're seeking an engineer strong in distributed systems, scalable data pipelines, and real-time ML applications.

Key Responsibilities
Data Engineering (Primary Focus)

  • Build large-scale batch and streaming pipelines using Dataflow, Pub/Sub, BigQuery, and Airflow/Composer.
  • Implement data governance practices including validation, quality monitoring, and anomaly detection.
  • Optimize data storage, indexing, and retrieval performance to support search and recommendation workloads.

Search / Recommendation System Enablement

  • Support data workflows and feature engineering for retrieval, ranking, and vector-based search systems.
  • Work with Feature Store, Vector DB, and embedding pipelines to boost relevance and performance.
  • Contribute to online serving strategies, A/B testing, and experiment design.

MLOps & AI Infrastructure

  • Develop end-to-end ML pipelines using Vertex AI, Kubeflow, and CI/CD automation.
  • Implement model versioning, A/B tests, data/model drift detection, and automated rollback mechanisms.
  • Enhance real-time and batch feature computation efficiency.

Cloud Architecture & Backend Engineering

  • Build scalable cloud architecture using GKE, Managed Instance Groups, and Cloud Run to handle burst traffic.
  • Develop low-latency, high-throughput APIs using Python (FastAPI).
  • Integrate multiple storage systems (BigQuery, Redis, Vector DB) and establish observability with Prometheus/Grafana.

Required Qualifications

  • 3–5 years of experience in Data Engineering / Backend / Platform development.
  • Strong proficiency in Python and experience with FastAPI.
  • Hands-on expertise with GCP services: GKE, MIG, Cloud Run, BigQuery, Pub/Sub, Dataflow.
  • Solid experience in distributed systems, high-throughput data processing, or burst-traffic scenarios.
  • Strong skills in Docker, Kubernetes, Helm, HPA, and CI/CD automation.

Preferred Qualifications (Nice-to-Have)

  • Experience building or supporting search or recommendation systems.
  • Exposure to Feature Store, Vector DB, embeddings, RAG, or LLM-based systems.
  • Experience operating systems with 10M+ daily requests or extreme peak loads.
  • Familiarity with IaC tools such as Terraform.

Why This Role

  • Work on high-impact systems powering millions of daily users.
  • Collaborate with teams building search, recommendation, and AI-driven product experiences.
  • Play a leading role in designing the next generation of data & ML infrastructure.
  • Join a company with a strong data culture, complex engineering challenges, and long-term scalability goals.

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