Senior Process Modelling Specialist

The Nestlé Deep Tech Center is where we develop and evaluate cutting-edge technologies to accelerate Nestlé’s global innovation mission and shape the future of food eraging advanced robotics and sensor technologies, AI, machine learning and digital twins, we are driving smarter manufacturing, delivering breakthrough consumer experiences, and maximizing our research and innovation capabilities. Every project here connects you to Nestlé’s purpose: unlocking the power of food to enhance quality of life for individuals, families, communities, and the planet, today and for generations to come.

Based in Orbe, Switzerland, and complemented by our Deep Tech Hub in Shenzhen, China, our state-of-the-art facility fosters a collaborative working environment, with creative spaces, rapid‑prototyping labs, automated kitchens, and pilot plants, so innovation moves fast from concept to reality.

Ready to build technology that matters? Join us and be a force for good!

Location:

Orbe (near Lausanne), Switzerland

Company:
Nestlé Deep Tech Center

Act. Rate:
Full-Time Act. Rate 100%
Type of contract:
Permanent contract

Start date:

As soon as possible

Exciting opportunities to develop your career your way; across different brands, businesses, functions, and regions.

Flexible working arrangements - facilitating creativity and collaboration.

A culture of respect, with diversity, equity and inclusion at its core. Learn more here.

A dynamic international environment empowering you to learn, develop and grow.

Don’t hesitate to connect with us during the recruitment process to learn more.

The Nestlé Deep Tech Center is looking for a Senior Process Modelling Specialist responsible for developing and applying advanced modelling and optimization techniques to support our R&D process automation initiatives. This is a novel, pivotal role with broad latitude to shape the future of simulation and modelling at Nestlé: you will design innovative approaches combining AI, hybrid statistical/mechanistic models, digital twins, simulation, and accelerated computation.

Embedded within a high-performing team of scientists and engineers, the role includes scouting emerging tools, assessing capabilities, and creating new methodologies for process modelling and optimization. As a key member of the Deep Tech Center, you will explore the frontiers of enabling technology and have a direct role in shaping adoption and impact with planetary-scale reach.

• Explore novel hybrid modelling approaches using AI/ML, digital twins, and classical techniques.
• Provide modelling, control and simulation support for projects, ensuring timely and impactful results aligned with priorities.
• Work with ML scientists, data engineers, and process experts to guide build‑vs‑buy decisions.
• Contribute to knowledge sharing by monitoring research and engaging with internal networks.
• Collaborate closely with stakeholders and technical teams to integrate solutions effectively.
• Prepare technologies for industrialisation in factories and markets, addressing potential issues proactively.
• Develop and implement digital standards to drive consistency and innovation.
• Ensure compliance with health, environment, and food safety policies, promoting safety by design principles.

• Master’s or PhD in Engineering, Physics, Applied Math, Computer Science, or related quantitative discipline.
• Proven experience in modelling, control, or automation within manufacturing or industrial environments.
• Familiarity with mechanistic modelling techniques (APM, CFD, FEA, DEM, logistics modelling).
• Experience with the application of digital twins both in simulation and in deployed applications for the control & optimization of industrial processes would be a strong plus.
• Exposure to simulation environments like NVIDIA Omniverse / Isaac Sim, or Mu Jo Co  is a plus.
• Strong proficiency with Python and basic software development practices; adept at data manipulation and analysis.
• Knowledge of instrumentation, process control, and industrial communication systems.
• Understanding of statistics and…