ASML is looking for a Machine Learning & AI Ops Engineer to build scalable infrastructure for developing, deploying, monitoring, and maintaining AI systems, ensuring the reliability, performance, and automation of AI-driven applications.
Requirements
- 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.
- ML & AI infrastructure
- Python
Responsibilities
- Design, 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.
Other
- 5+ years of experience in ML and/or AI Ops.
- Bachelor’s or Master’s degree in Computer Science or related field.
- We are looking for a skilled and forward-thinking Machine Learning & AI Ops Engineer to join our team.
- You will collaborate with cross-functional teams to ensure the reliability, performance, and automation of AI-driven applications.
- Maintain documentation and best practices for ML and AI Ops processes.
