Software Engineer - Scientific Computing & AI (.NET/Windows)

KLA CORPORATION Chennai, Tamil Nadu
Permanent Job Not disclosed
computational workflows Modelling AI-assisted development tools

KLA Corporation, a global leader in semiconductor manufacturing technology, is seeking a highly motivated Software Engineer to join our Advanced Computing Labs (ACL) in Chennai. You will contribute to pioneering research and software architectures for AI, High-Performance Computing (HPC), and Cloud solutions that accelerate KLA's products. This role focuses on scientific computing and modeling, requiring strong development skills on the .NET/Windows platform using C# or C++. You will collaborate with scientists and engineers to design, develop, and optimize software for modeling and computational workflows, translating complex requirements into robust, scalable, and high-performance solutions. Experience with AI-assisted development tools is a plus.

Key Responsibilities:

  • Design, implement, and maintain software applications using C# or C++ on the .NET/Windows platform.
  • Collaborate with scientists and engineers to translate modeling and computational requirements into robust software solutions.
  • Develop scalable, performant, and maintainable software for computationally intensive applications.
  • Optimize code for performance, scalability, and efficiency in scientific computing environments.
  • Participate in code reviews, testing, debugging, and validation.

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • 8+ years of professional software development experience.
  • Proficiency in C# or C++, with strong knowledge of the .NET framework and Windows development.
  • Proven ability to deliver medium-to-large scale software systems.
  • Experience in scientific computing, modeling, or computationally intensive applications.
  • Strong problem-solving skills and ability to work independently and collaboratively.
  • Experience with AI-assisted development tools is preferred.

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