Company Overview
KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices.
Group/Division
The Information Technology (IT) group at KLA is involved in every aspect of the global business. IT’s mission is to enable business growth and productivity by connecting people, process, and technology. It focuses not only on enhancing the technology that enables our business to thrive but also on how employees use and are empowered by technology. This integrated approach to customer service, creativity and technological excellence enables employee productivity, business analytics, and process excellence.
Job Description/Preferred Qualifications
We are seeking a highly skilled Software Engineer with specialized expertise in Machine Learning, Artificial Intelligence, and Data Science to join our innovative technology team. This role will be key in developing impactful AI solutions that drive business transformation and technological advancement. The ideal candidate will combine strong technical skills with business intelligence to translate complex requirements into practical, scalable applications that deliver measurable impact.
Key Responsibilities:
- AI/ML Solution Development: Design, develop, and implement machine learning models and AI algorithms to address business challenges. This includes data preprocessing, model training, validation, and deployment.
- Scalable Architecture Design: Architect and design scalable systems that can handle large volumes of data and complex AI/ML workloads, ensuring high performance and reliability.
- Production-Ready Solutions: Implement AI/ML solutions that are robust, maintainable, and ready for production environments. This includes considerations for security, compliance, and operational efficiency.
- Innovation and Research: Stay abreast of the latest developments in AI, ML, and data science. Conduct research to explore new methodologies or improve existing ones, ensuring our solutions remain innovative.
- Collaboration: Work closely with multi-functional teams including data engineers, product managers, software developers, and business partners to integrate advanced solutions into our products and services, ensuring alignment with business objectives.
- Problem Solving: Apply critical thinking to solve complex problems, often requiring innovative approaches to data analysis, model architecture, system integration, and business strategy.
- Deployment and Monitoring: Oversee the deployment of AI/ML models into production environments, ensuring scalability, performance, and reliability. Monitor model performance post-deployment and iterate as necessary.
- Documentation and Knowledge Sharing: Document processes, methodologies, and findings. Share knowledge through internal presentations, workshops, or by contributing to our knowledge base.
Minimum Qualifications
- Bachelor's degree in Computer Science, Data Science, AI, or a related field. Master's and/or PhD preferred.
- Minimum of 3-5 years of experience in AI/ML, with a proven track record of deploying solutions in a production environment.
- Proficiency in Python, or similar languages, with experience in libraries like TensorFlow, Scikit-learn, etc. Experience with RAG is essential.
- Strong background in statistics, machine learning algorithms, deep learning, neural networks, and system architecture.
- Strong understanding of cloud platforms, DevOps practices, and data processing technologies.
- Demonstrated ability to lead technical projects and work effectively in matrix environments.
- Ability to communicate technical concepts to non-technical team members and business partners.
- Familiarity with software engineering best practices, including version control (Git), CI/CD pipelines, agile methodologies, and system design patterns.
Preferred
- Experience with specialized AI domains or industry-specific applications.
- Contributions to open-source projects or research publications in AI/ML.
- Knowledge of AI ethics and responsible AI practices.