About the role
Responsibilities:
- Build and lead a team of software engineers to develop robust and scalable software for wafer inspection products, leveraging modern software practices and machine learning.
- Drive the evolution of next-generation software architecture while supporting and enhancing existing software platforms.
- Acquire and demonstrate technical expertise in LS-SWIFT product software.
- Deliver high-quality software within product timelines.
- Work on complex technical challenges requiring in-depth analysis and evaluation of multiple factors.
- Ensure software designs, code, and unit testing are robust, scalable, maintainable, and future-ready.
- Identify and implement architectural and design improvements to existing software.
- Continuously learn and adopt new software technologies independently.
- Work effectively with both legacy frameworks and modern technologies.
- Collaborate with cross-functional and globally distributed engineering teams to develop and deliver software solutions.
- Communicate effectively on both technical and business topics.
Requirements:
- Strong programming skills using high-level languages such as Java, Python, C#, and C++.
- Strong understanding of software design principles and architectural patterns.
- Good knowledge of open-source software and various technologies across web and thick client applications, with an understanding of their architectural strengths and limitations.
- Passion for building, mentoring, and developing engineering teams.
- Strong analytical thinking and decision-making skills for technical and project-related challenges.
- Excellent technical problem-solving abilities.
- Functional management experience is not mandatory.
- Experience in semiconductor processing, the semiconductor equipment industry, or product-based organisations is preferred.
- Excellent communication, organisational, analytical, leadership, and interpersonal skills.
- Self-driven with the ability to work effectively in a collaborative team environment.
- Good understanding of High-Performance Computing (HPC), including CPU/GPU performance concepts and related technologies.
- Basic understanding of machine learning concepts.