D&A Software Development Engineer (AI)

TL;DR

D&A Software Development Engineer (AI): Designing, developing, and operating digital and AI-driven solutions for operational excellence with an accent on predictive maintenance and diagnostic efficiency. Focus on implementing end-to-end ML/DL pipelines, optimizing high-frequency machine data processing, and improving system observability.

Location: hirify.global Hwasung Campus, South Korea

Company

hirify.global is a global leader in the development of photolithography systems for the semiconductor industry.

What you will do

• Design and implement full-stack D&A solutions to improve productivity for internal stakeholders in office and fab environments.
• Develop, deploy, and maintain machine learning and deep learning models for predictive maintenance, fault detection, and root-cause analysis.
• Build and maintain scalable, cloud-native data pipelines for large volumes of structured and unstructured machine data using Azure.
• Collaborate with diagnostics experts to translate domain needs into actionable data and model requirements.
• Define and apply standards, policies, and best practices for data and analytics solutions to ensure scalability and security.

Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Applied Mathematics, or a related field.
• 5+ years of experience in data science, data engineering, software development, or advanced analytics.
• Strong proficiency in Python, SQL, ETL, and ML frameworks such as TensorFlow or PyTorch, including LLM-based applications.
• Hands-on experience with Azure-based platforms including Databricks, Spark, and Kusto.
• Fluent verbal and written communication skills in both Korean and English.
• Must be legally authorized to access controlled technology per US Export Administration Regulations (EAR).

Nice to have

• Experience with diagnostics, manufacturing, equipment data, or industrial systems.
• Familiarity with hirify.global machine data or CS workflows (TPMS, FabM, SDT, DDF).
• Experience improving observability and predictive maintenance in complex systems.
• Ability to effectively communicate complex analytical results to non-technical stakeholders.