Engineer

KLA is a world leader in diversified electronics, integral to the semiconductor manufacturing ecosystem. Our technologies power virtually every electronic device. We invent systems and solutions for manufacturing wafers, reticles, integrated circuits, packaging, printed circuit boards, and flat panel displays. With a strong commitment to innovation, KLA invests significantly in research and development, fostering collaborative teams of physicists, engineers, and data scientists. Join us in tackling complex challenges and advancing tomorrow's electronic devices.

The Global Products Group (GPG) at KLA, responsible for creating metrology and inspection products, is seeking talented individuals. Central Engineering, KLA's largest engineering organization, comprises Centers-of-Excellence (CoE) in various disciplines, including Handling & Automation, Precision Motion Control, Sensors & Image Acquisition, Platform Design, and Packaging Engineering. Our global team of over 500 engineers across Israel, China, India, and the US drives innovation and delivers expertise across all product groups.

We are looking for a skilled MLOps Site Reliability Engineer (SRE) to ensure the reliability, scalability, and performance of our machine learning infrastructure. You will collaborate with data scientists, ML engineers, and software developers to build and maintain robust systems supporting our ML workflows. This role offers an opportunity to work with cutting-edge technologies and significantly impact our organization's success.

Responsibilities:

• Design, implement, and maintain scalable and reliable machine learning infrastructure.
• Collaborate with data scientists and machine learning engineers on deploying and managing ML models in production.
• Develop and maintain CI/CD pipelines for machine learning workflows.
• Monitor and optimize the performance of machine learning systems and infrastructure.
• Implement and manage automated testing and validation processes for ML models.
• Ensure the security and compliance of ML systems and data.
• Troubleshoot and resolve issues related to ML infrastructure and workflows.
• Document processes, procedures, and best practices for machine learning operations.
• Stay current with MLOps and related technological advancements.

Required Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience as a Site Reliability Engineer (SRE) or in a similar role.
• Strong understanding of machine learning concepts and workflows.
• Proficiency in programming languages like Python, Java, or Go.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with containerization technologies like Docker and Kubernetes.
• Experience with CI/CD tools such as Jenkins, GitLab CI, or CircleCI.
• Excellent problem-solving skills and ability to troubleshoot complex issues.
• Strong communication and collaboration skills.

Preferred Qualifications:

• Master's degree in Computer Science, Engineering, or a related field.
• Experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Knowledge of data engineering and data pipeline tools such as Apache Spark, Apache Kafka, or Airflow.
• Experience with monitoring and logging tools like Prometheus, Grafana, or ELK stack.
• Familiarity with infrastructure as code (IaC) tools like Terraform or Ansible.
• Experience with automated testing frameworks for machine learning models.
• Knowledge of security best practices for machine learning systems and data.

Minimum Qualifications: A Master's degree or a Bachelor's degree with 2 years of related work experience.