Development Engineer: Applied AI/ML and Intelligent systems

About VAT Group
At VAT, we change the world with vacuum solutions. As the world's leading supplier of high-performance vacuum valves, we have been driving innovation for more than 60 years. With over 3,200 employees worldwide, we operate from our headquarters in Haag, Switzerland, with manufacturing sites in Switzerland, Malaysia and Romania, as well as sales and service hubs around the world. We guided by our passions integrity, teamwork, customer centricity, and innovation - always working together as #oneVAT.
Joining us means becoming part of a passionate, international team where your voice is heard, your ideas matter, and your career growth is supported.
Development Engineer: Applied AI/ML and Intelligent systems
YOUR CHALLENGES
Our products are key components in any semiconductor processing tool worldwide. To extend our market leadership in advanced pressure control for sub-2 nm chip production we want to strengthen our team with experienced engineers and researchers with a passion for applied AI/ML, system modelling, data driven engineering and intelligent systems.
You will be an integral part of our team and drive advanced R&D in the following areas: industrial time-series analytics, statistical machine learning, AI/ML infrastructure and toolchains, Generative AI applications, AI agents, multimodal data fusion, or Edge AI deployment for smart semiconductor manufacturing equipment.
You are a great fit for our team if you want to work at the forefront of applied AI/ML for semiconductor hardware control. You enjoy taking initiative, exploring new approaches to intelligent control systems, and validating your ideas hands-on in real experimental and industrial environments.
YOUR COMPETENCIES
Required Baseline
MSc or PhD in data science and machine learning, physics, mathematics, mechanical engineering, electrical engineering, control engineering, mechatronics, chemical engineering or a related field
Expertise in one or more focus areas: applied AI/ML domains, such as time-series machine learning, statistical machine learning, Generative AI, multimodal AI, AI agents, Edge AI, or ML infrastructure.
Strong programming skills in Python, with experience in scientific computing, data processing, model development, and software engineering best practices.
Experience with industrial or sensor-based data, including time-series signals, process data, logs, recipes, or equipment data.
Ability to develop AI/ML solutions from concept to prototype, including data preparation, model development, validation, deployment, and documentation.
Expertise in one or more focus area profile
Industrial time-series machine learning, anomaly detection, prediction, classification, regression, or process monitoring.
Statistical machine learning, uncertainty estimation, model validation, feature engineering, or data-driven decision-making.
AI/ML infrastructure and MLOps, including experiment tracking, model versioning, CI/CD, containerization, monitoring, or scalable data/model pipelines.
Advanced machine learning for industrial applications using Python, MATLAB, or Simulink.
Additional experience is plus
Generative AI, including foundation models, retrieval-augmented generation, synthetic data generation, or AI-assisted engineering workflows.
AI agents or agentic workflows, including tool-using agents, workflow automation, orchestration frameworks, or LLM-based assistants.
Multimodal AI, combining heterogeneous data sources such as signals, images, text, logs, recipes, and equipment metadata.
Edge AI, including model compression, lightweight inference, embedded deployment, real-time constraints, or industrial hardware integration.
Know-how in vacuum systems, semiconductor equipment, process control, or deployment of ML models on real hardware.
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