Machine Learning Engineer – Industrial Innovation

Create a better #TomorrowWithUs

At Siemens, we build technology solutions to shape the world we live in. We transform industries and societies by combining the real and digital worlds. With over of the world's most forward-thinking minds and the power of a presence in more than 190 countries, we make a truly global impact.

At the Portugal Tech Hub, we take on challenges to make life easier, safer, and more sustainable for us and generations to come. We bring value to the business digitalization transition, from Portugal to the world, in areas such as Artificial Intelligence, Analytics & Business Intelligence, Application Lifecycle Management, Cybersecurity, IT Infrastructure Management, IT Project & Service Management, IT Strategy, User Experience, and many more.

With a decade of history and around 1.600 experts, the Portugal Tech Hub is the home of the new technologists – Dream Builders, Impact Creators & Future Makers.

Are you one of them? Come join us

About Siemens Foundational Technologies Department

Siemens Foundational Technology is the central in-house R&D unit at Siemens and as such is an integral part of Siemens' innovation ecosystem.

It acts as a strategic partner to support Siemens' business units with R&D services, contributes to the company's intellectual property portfolio, and coordinates the collaboration with top universities worldwide.

Through its R&D activities in Germany, USA, Portugal, China, India, and Eastern Europe, Siemens Foundational Technology helps to ensure the company's technological future.

Transforming our future starts with every day

Your mission will be…

This role is an opportunity for a seasoned machine learning engineer passionate about applying Deep Learning and advanced analytics to industrial innovation. You will lead the development of AI-driven solutions in areas such as industrial copilots, foundation models, intelligent monitoring systems and industrial computer vision. The position demands creativity, technical excellence, and a strong drive to push the boundaries of applied AI in real-world industrial contexts.

What are the responsibilities?

• Lead the design, development, and deployment of advanced analytics components within industrial systems, with a focus on Generative AI, LLMs, computer vision, and signal processing.
• Architect and implement Deep learning-powered solutions such as industrial copilots, intelligent assistants, and synthetic data generators for engineering and operational use cases.
• Fine-tune and evaluate LLMs and generative architectures (e.g., transformers, GANs, VAEs, diffusion models) for industrial domain.
• Develop RAG pipelines and agentic workflows to enhance model performance and usability.
• Collaborate with cross-functional teams including software engineers, MLOps specialists, and domain experts to deliver scalable, production-ready AI solutions.
• Conduct feasibility studies, rapid prototyping, and experimental research to validate new ideas and technologies.
• Contribute to thought leadership through publications, patents, internal workshops, and external presentations.
• Mentor junior team members and foster a culture of innovation and continuous learning.

We are looking for someone with…

Would be beneficial to have experience with :

What you can expect from us…

A hybrid and flexible working model to promote a better work-life balance, along with a budget for home office support and the opportunity to do 16 hours a year of volunteer work. A health insurance, access to our on-site medical center, plus the chance to join sports groups.

In addition, you'll have access to online learning platforms and discounts with our partners. A shuttle bus to commute to the facilities and the possibility of financial support to your studies.

What makes us proud as an employer :

Please attach your CV in English.

#Siemens #PortugalTechHub

Siemens is committed to creating a diverse environment and is glad to be an equal opportunity employer. We strongly encourage applications from a diverse talent pool