EDA Tools Software Engineer

TL;DR

EDA Tools Software Engineer (AI/ML): Designs, develops, tests, and maintains software tools, workflows, and methodologies for design automation in hardware product design and manufacturing with an accent on data analytics, AI/ML integration, and agentic AI development. Focus on translating business requirements into scalable AI-enabled solutions, Power BI dashboards, data transformation, and issue management system enhancements.

Location: Hybrid in Penang, Malaysia (must work on-site at assigned hirify.global site)

Company

hirify.global's Central Engineering Group builds scalable engineering solutions for product enablement, custom ASIC, and foundry services.

What you will do

• Contribute to AI/ML use cases including data preparation, model integration, and performance analysis.
• Design, develop, and maintain Power BI reports and dashboards for analytics.
• Transform and model data into actionable insights using AI techniques.
• Administrate and enhance the issue management ticketing system.
• Collaborate with cross-functional stakeholders to deliver scalable solutions.
• Identify opportunities to improve automation, analytics, and efficiency.

Requirements

• Hybrid work model requires splitting time between on-site in Penang, Malaysia and off-site
• B.S. or M.S. in Computer Science, Computer Engineering, Electrical Engineering, Data Science, or related.
• 2-3 years in software development, data engineering, analytics, or AI roles.
• Hands-on experience with AI/ML concepts, frameworks, or use cases.
• Strong Python and SQL programming; Windows/Unix/Linux environments.
• Understanding of RDBMS, data structures, algorithms.

Nice to have

• Power BI, Power Apps, DAX experience.
• Machine Learning workflows, data modeling, modern analytics platforms.
• Web development with HTML/JavaScript; Git, JIRA, Jenkins, CI/CD, Splunk, TDD.
• Code quality analysis, software metrics.

Culture & Benefits

• Fast-paced, collaborative environment.
• Self-motivated work with project rotation for technical growth.
• Hybrid work model flexibility.
• Focus on measurable business impact and short development cycles.