[집중채용] Senior AI Data Pipeline Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Design and operate high-throughput, scalable data pipelines that ingest and process worldwide data and reliably deliver petabyte-scale datasets to large-scale GPU infrastructure for mission-critical AI workloads. Architect multi-region data infrastructure, build flexible branching logic for concurrent AI projects, optimize processing with Databricks and Spark, and maintain Kubernetes-based containerized data environments. Collaborate with AI researchers and platform teams to power training and evaluation pipelines.

Location: South Korea

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and build high-performance, scalable data pipelines to support diverse AI and machine learning initiatives.
•Architect and implement multi-region data infrastructure to ensure global availability and seamless synchronization.
•Develop flexible pipeline architectures that enable complex branching and logic isolation for concurrent AI projects.
•Optimize large-scale data processing workloads using Databricks and Spark to maximize throughput and minimize processing costs.
•Maintain and evolve the containerized data environment on Kubernetes and collaborate with AI researchers and platform teams to feed training and evaluation pipelines.

Key Requirements

•Build and operate production-grade data pipelines for massive-scale AI/ML datasets.
•Strong proficiency in distributed processing frameworks, particularly Apache Spark and the Databricks ecosystem.
•Hands-on experience with workflow orchestration tools like Apache Airflow to manage complex dependencies.
•Deploy and scale data processing components using Kubernetes and containerization.
•Understand high-throughput data ingestion and event-driven architectures using Apache Kafka.

Experience:AIML

Skills:Problem-solvingCommunicationCollaboration

Tech Stack:Apache SparkDatabricksApache AirflowKubernetesContainersApache KafkaPythonGPUSpark StreamingFlinkRayTerraform

Company Brief

42dot

Website

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42dot

1 week ago

[집중채용] Senior AI Data Pipeline Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: South Korea

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and build high-performance, scalable data pipelines to support diverse AI and machine learning initiatives.
•Architect and implement multi-region data infrastructure to ensure global availability and seamless synchronization.
•Develop flexible pipeline architectures that enable complex branching and logic isolation for concurrent AI projects.
•Optimize large-scale data processing workloads using Databricks and Spark to maximize throughput and minimize processing costs.
•Maintain and evolve the containerized data environment on Kubernetes and collaborate with AI researchers and platform teams to feed training and evaluation pipelines.

Key Requirements

•Build and operate production-grade data pipelines for massive-scale AI/ML datasets.
•Strong proficiency in distributed processing frameworks, particularly Apache Spark and the Databricks ecosystem.
•Hands-on experience with workflow orchestration tools like Apache Airflow to manage complex dependencies.
•Deploy and scale data processing components using Kubernetes and containerization.
•Understand high-throughput data ingestion and event-driven architectures using Apache Kafka.

Experience:AIML

Skills:Problem-solvingCommunicationCollaboration

Tech Stack:Apache SparkDatabricksApache AirflowKubernetesContainersApache KafkaPythonGPUSpark StreamingFlinkRayTerraform

Company Brief

42dot

Website