30+ days ago - req21035
Machine Learning Engineer / Data Engineer
Research & development
In a nutshell
Research & development
Data science is a broad and demanding domain, and typically data scientists come from a 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.
As a Machine Learning Engineer you will apply the latest technologies and tools to implement complex machine learning models. You will lead the path towards implementing solutions built with data scientist and integrate them with various Big Data platforms and architectures. You will be responsible for creating and maintaining Machine Learning pipelines that are scalable, robust, and ready for production. To achieve this, you will be closely working with domain experts, platform architects, IT specialists, software developers, data scientists and data engineers from various parts of the organization. On top of your profound technical capabilities, your success will strongly dependent on your interpersonal skills and your ability to communicate across disciplines to bridge the gap between data science and software engineering.
You will be working in a multi-disciplinary team of data scientists, data engineers, machine learning engineers, physicists, computer scientists, and 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.
At least University Bachelor’s qualification in Software Engineering, Computer Science, Data Science or equivalent and proven Machine Learning Operations (MLOps) competence.
An important aspect of the role is to build and deploy scalable machine learning pipelines using
containerization and orchestration technologies like Docker and Kubernetes, requiring:
- Proven track record with 3+ years experience in developing pipelines for preprocessing large volumes of image and sensor data using scalable frameworks like PySpark
- Strong programming skills in one or more programming languages like Python, Java, or Scala
- 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
- Experience in building machine learning models using frameworks like: Scikit-learn, XGBoost, TensorFlow, Pytorch, etc.
- Familiar with relational and non-relation database systems like: MongoDB, Impala, DeltaLake, etc.
- Experience on productizing machine learning models on Cloud platforms like AWS, Azure, or GCP
- Experience with microservice architectural patterns
- Good communicator, who can connect across disciplines
- Team player, who exhibits ownership and is pro-active and customer-oriented
- Quality-driven, can-do, supportive mentality
- 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
In return we provide:
- Work in an open constructive environment with a 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
Context of the position
Within ASML, the sector Development & Engineering is responsible for the development, specification and design of new ASML products.
Within Development & Engineering, the CSI department delivers and advances state-of-the- art methods and techniques for the structural improvement of the performance and quality of scanner components.
The holder of this position reports to the manager of CSI Data Science & Engineering group.
Please, make sure to provide a motivation letter along with your resume.