Machine Learning Engineer

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 300,000 of the world’s most forward-thinking minds and a presence in more than 190 countries, we make a truly global impact. About the role 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. 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 domains. 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. Qualifications Master’s or PhD in Computer Science, Data Science, Mathematics, Engineering, or a related field. 5+ years of commercial experience in data science, with at least 2 years focused on Generative AI or LLMs. Strong proficiency in Python and deep learning frameworks (e.G., PyTorch, TensorFlow, Hugging Face). Hands‑on experience with fine‑tuning foundation models (e.G., GPT, LLaMA, Mistral) and building Generative AI applications. Familiarity with prompt engineering, RAG systems, and vector databases. Experience with cloud platforms (AWS preferred), containerization (Docker), and MLOps tools (e.G., Airflow, DVC, ClearML). Solid understanding of signal processing, time series analysis, and computer vision. Proven ability to handle large‑scale, heterogeneous industrial datasets. Excellent communication skills and ability to translate complex technical concepts into actionable insights. Strong motivation for applied research and innovation in industrial domains. Beneficial Experience Contributions to open‑source deep‑learning projects or relevant publications. Successful participation in AI competitions (e.G., Kaggle). Experience with industrial domains such as energy, manufacturing, or infrastructure. What we offer A hybrid and flexible working model to promote a better work‑life balance, a budget for home office support, and the opportunity to do 16 hours a year of volunteer work. You will enjoy health insurance, access to an on‑site medical center, sports group participation, online learning platforms, partner discounts, a shuttle bus to commute to the facilities, and financial support for your studies. Why Siemens Merco – Companies and Leaders with the Best Reputation in Portugal (#1 Technology/Manufacturing) Forbes – World’s Best Employers (#1 Engineering & Manufacturing) LinkedIn – LinkedIn Top Companies (#2) OnStrategy – REPSCORE 2024: Brands’ Reputation in Portugal (#1 Engineering & Electronic Services) Fortune – World’s Most Admired Companies (#1 Industrial Machinery) Teamlyzer – Company with the Best Interviews (#1 Technology) 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 #J-18808-Ljbffr