ASML Senior Software Engineer - AI Infrastructure Edit ...

## About ASMLAt ASML, we push the boundaries of technology to enable groundbreaking progress in the semiconductor industry. As the world’s leading supplier of lithography systems, we provide chipmakers with the hardware, software, and services they need to mass-produce ever-smaller, faster, and more energy-efficient microchips. Headquartered in the Netherlands, ASML operates at the cutting edge of physics, mechatronics, optics, and software. Our innovations power the devices that shape modern life—smartphones, computers, medical equipment, and countless other technologies that connect, inform, and improve the world around us. With a global workforce of over 40,000 employees from more than 140 nationalities, we thrive on diversity, creativity, and collaboration. Our culture encourages curiosity, bold ideas, and a relentless drive to make the impossible possible. At ASML, we don’t just build machines—we build the future of technology. By continuously innovating and partnering with leading chip manufacturers, we play a crucial role in advancing Moore’s Law and creating the next generation of digital solutions.## About the RoleWe are looking for a skilled and forward-thinking Machine Learning & AI Ops Engineer to join our team. This hybrid role combines the responsibilities of MLOps and AI Ops, focusing on building scalable infrastructure for developing, deploying, monitoring, and maintaining AI systems. You will collaborate with cross-functional teams to ensure the reliability, performance, and automation of AI-driven applications.## QualificationsBachelor’s or Master’s degree in Computer Science or related field. 5+ years of experience in ML and/or AI Ops. Proficiency with ML/AI model lifecycle management (e.g., MLflow). Expertise with ML/AI frameworks (e.g., PyTorch) and model serving frameworks (e.g. Triton). Expertise with containerization (Docker, Kubernetes) and orchestration tools. Experience with LLMs, code intelligence, or AI-assisted development tools.## ResponsibilitiesDesign, implement, and maintain end-to-end ML pipelines for training, inference, deployment, and monitoring. Build and manage scalable, reliable, and secure data pipelines for ingesting, transforming, and storing structured and unstructured data. Automate model deployment and lifecycle management using CI/CD tools and frameworks. Collaborate with algorithm engineers to productize ML workflows for e-beam inspection and metrology. Design and build scalable, high-performance infrastructure to support AI-based software development automation. Develop and maintain data pipelines for collecting, processing, and storing code, telemetry, and developer activity data. Collaborate with AI researchers and engineers to deploy and operationalize LLMs and other AI models in production environments. Maintain documentation and best practices for ML and AI Ops processes. #J-18808-Ljbffr

Created: 2025-09-18