Eda Tools Software Engineer

Intel Intel · Semiconductors · Penang, Malaysia

This role focuses on designing, developing, and maintaining software tools and workflows for design automation, with a strong emphasis on data analytics and AI/ML. It involves contributing to AI/ML use cases, data preparation, model integration, and potentially agentic AI development. The role also includes transforming data into insights using AI techniques and developing analytics dashboards.

What you'd actually do

  1. Contribute to AI/ML use cases, including data preparation, model integration, and performance analysis.
  2. Stay current with AI and Machine Learning trends, tools, and best practices, including emerging frameworks and enterprise AI adoption patterns.
  3. Design, develop, and maintain Power BI reports and dashboards for business and engineering analytics.
  4. Transform, automate, and model data into actionable insights using business analytics and AI techniques.
  5. Collaborate closely with cross functional stakeholders to deliver robust, scalable, and maintainable solutions.

Skills

Required

  • Python
  • SQL
  • Windows
  • Unix/Linux environments
  • relational database (RDBMS)
  • data structures
  • algorithms
  • AI / Machine Learning concepts
  • AI / Machine Learning frameworks
  • applied AI/ML use cases

Nice to have

  • C
  • C++
  • C#
  • Perl
  • Power BI
  • Power Apps
  • DAX
  • Machine Learning and AI workflows
  • data modelling
  • modern analytics platforms
  • web development
  • HTML
  • JavaScript
  • Git
  • JIRA
  • Jenkins
  • CI/CD pipelines
  • Splunk
  • Test Driven Development (TDD)
  • code quality analysis
  • software metrics
  • maintainability practices

What the JD emphasized

  • practical industry experience in data analytics and AI
  • strong understanding of current and emerging AI/ML trends
  • apply these technologies to real world business and engineering problems
  • agentic AI development
  • Hands on experience with AI / Machine Learning concepts, frameworks, or applied use cases.
  • Demonstrated ability to apply AI or analytics solutions to business or engineering problems.

Other signals

  • AI/ML use cases
  • data preparation
  • model integration
  • performance analysis
  • agentic AI development
  • transform, automate, and model data into actionable insights using business analytics and AI techniques