Manager, Software Development
Indexed description
Group/Division
With over 40 years of semiconductor process control experience, chipmakers around the globe rely on KLA to ensure that their fabs ramp next-generation devices to volume production quickly and cost-effectively. Enabling the movement towards advanced chip design, KLA's Global Products Group (GPG), which is responsible for creating all of KLA’s metrology and inspection products, is looking for the best and the brightest research scientist, software engineers, application development engineers, and senior product technology process engineers. The LS-SWIFT Division of KLA’s Global Products Group provides patterned wafer inspection systems for high-volume semiconductor manufacturing. Its mission is to deliver market-leading cost of ownership in defect detection for a broad range of applications in the production of semiconductors. Customers from the foundry, logic, memory, automotive, MEMS, advanced packaging and other markets rely upon high-sample wafer inspection information generated by LS-SWIFT products. LS (Laser Scanning) systems enable cost-effective patterned wafer defect detection for the industry’s most sophisticated process technologies deployed in leading-edge foundry, logic, DRAM, and NAND fabs. SWIFT (Simultaneous Wafer Inspection at Fast Throughput) systems deliver all-wafer-surface (frontside, backside, and edge) macro inspection that is critical for automotive IC, MEMS, and advanced packaging processes as well as foundry/logic and memory fabs. LS-SWIFT operates from a global footprint that includes the US, Singapore, India and Germany, and serves a worldwide customer base across Asia, Europe and North America.
Job Description/Preferred Qualifications
Job Requirements:
- Strong understanding of programming skills using high-level languages - Java, Python, C#, C++,
- Strong knowledge of Design & Architectural patterns
- Good knowledge on Open source software and varied technologies (web and thick client). Have a good understanding on the strengths and weaknesses of software architectures of these technologies
- Passion for building and nurturing team members and help them realize full potential
- Rational thinking in arriving at a decision (technical or for project)
- Good technical problem-solving skills
- Functional manager experience is not a prerequisite
- Build and lead a team of smart software engineers to help our wafer inspection products to achieve the next level of performance through superior technology and the latest in software practices & machine learning. You will bring your proven experience in leading a team of engineers to conceive, design and deploy robust/scalable software for high-volume production and real time applications.
- Need to lead the change to bring in the next generation SW architecture (in possibly newer tech stack) along with supporting the existing set of features done with the current SW tech stack
- Acquire and demonstrate technical knowledge of LS-SWIFT product software
- Meet product timelines with good quality software
- Works on complex problems where analysis of situations or data requires an in-depth evaluation of various contributing factors
- Ensuring that detailed designs, code, and unit tests are consistent, robust, future-proof and scalable. Understand and make design and architectural improvements on existing software.
- Motivated to learn newer Software technologies independently
- Easily work with legacy frameworks, while embracing and implementing modern technologies and frameworks
- Collaborate with cross-divisional and cross-functional teams across geographical zones to develop / deliver software solutions
- Communicate effectively on technical and business topics
- Preferred work experiences in semiconductor processing / equipment industry or product companies
- Must have excellent communication, organizational, analytical, leadership, and interpersonal skills
- Must be self-driven, and a strong team player
- Good understanding on High Performance computing and related technologies/aids (CPU, GPU performance comparison and related toolkits) along with Machine learning basics
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