Machine Learning Engineer Predictive Maintenance

Job description


Introduction to the job

Data science is a broad and a demanding domain, and typically data scientists come from different background than software engineers. Most of the time, a data scientist is more focused on translating the business problem to a data science problem, and has less bandwidth to focus on all other aspects required to productize the machine learning model. As you can imagine, productizing a machine learning model comes with its own challenges like efficient coding, automation, monitoring, and scaling. This is where you come in. As a machine learning engineer at ASML, you will write efficient code to implement complex machine learning models and nurture them towards production to support the operation of the most complex lithography machines in the world.

You will be working in a multi-disciplinary team of data scientists, functional experts, data engineers, machine learning engineers, physicists, computer scientists, and IT engineers to build, deploy and maintain scalable Machine Learning pipelines on various Big Data platforms. The team has been developing powerful predictive and diagnostic software tools that are aiming to uncover causal relationships between complex lithography equipment parameters and system performance. In addition, the team is engaging on predictive solutions for condition-based maintenance and equipment health monitoring.

This position requires access to controlled technology, as defined in the Export Administration Regulations (15 C.F.R.

  • 730, et seq.). Qualified candidates must be legally authorized to access such controlled technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.

Role And Responsibilities

ML Engineer role and responsibilities.

An important aspect of the role is to build and deploy scalable machine learning pipelines using containerization and orchestration technologies like Docker and Kubernetes.

  • Personal skills:
  • Good and proactive communicator, who can connect across disciplines in an international environment
  • Team player, who exhibits ownership and is pro-active and customer-oriented
  • Quality-driven, can-do, supportive mentality, creative thinker
  • Eager to guide others, for instance data scientists for productization of machine learning models
  • Eager to learn, e.g. about new MLOps techniques and about the lithography domain
  • Experience with scrum/agile WoW
  • Enthusiastic and intrinsically motivated. Taking responsibility, ownership and self-propelling
  • Goal-oriented and flexible mindset, willing to acquire lithography and other semiconductor manufacturing knowledge

In return we provide:

  • Work in an open constructive environment with Multi-disciplinary team: Data scientists, data engineers and physicists
  • Build and deploy scalable ML pipelines to optimize some of the most complex machines known to mankind that drive the digitalization of the world

Education And Experience

At least University Bachelor’s qualification in Software Engineering, Computer Science, Data Science or equivalent and proven Machine Learning Operations (MLOps) competence.


  • Strong programming skills in one or more programming languages like Python
  • Proven track record with 3+ years experience in developing pipelines for preprocessing large volumes of image and sensor data using scalable frameworks like PySpark
  • Build and operate automated CI/CD pipelines for ML solutions (MLOps)
  • Proficient in development practices: git, CI/CD, unit testing
  • Experience with productization of machine learning models using popular frameworks such as Kubernetes, Airflow and Kubeflow


Additional qualifications for Predictive Maintenance development team:

Proven track record in designing, experimenting and building accurate and scalable Machine Learning models Ability to create fast prototypes – experiment and iterate towards ideal solution in an Agile/ CRISP-DM manner Experience in creating Kubeflow and Airflow pipelines (+++) Well versed with the latest GCP offerings like Vertex AI, BigQuery, dataprep Pub/Sub, DataProc (+++) and experience with Feature Store Ensuring data is available in the right format and reliable quality for other DS and ML colleagues. Working on improvements of the quality of data as well as challenges as data shift and concept drift Testing Data engineering pipelines at staging environments and deploying them at production Writing proprietary packages / frameworks to be used for internal purposes to make the standard tasks easier (such as active learning, MLOps2, exploratory data analysis, etc.) Nice to have: hands-on experience in working with ASML machine and performance data sets Nice to have: good knowledge and experience with database engineering, building and using optimally databases

Diversity and inclusion

ASML is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company.

Other Information

Within ASML, the sector Development & Engineering is responsible for the development, specification and design of new ASML products.

Within Development & Engineering, the DATA (DAta infrastructure, diagnostics Tooling and Analytics) department delivers and advances state-of-the- art methods and techniques for the monitoring, diagnostics and structural improvement of the performance and quality of scanner components using scanner data.

The holder of this position reports to the manager of Predictive Maintenance & Diagnostics group.

EOE AA M/F/Veteran/Disability

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