GenAI Software Engineer - Prototyper & Architect

Google Inc.; Zürich; Vor Ort; CHF 160.000 - 230.000; Vollzeit

Zusammenfassung

Google DeepMind is seeking a Share Software Engineer focused on Generative AI to push the boundaries of AI research and engineering in Zurich. You will contribute across modeling, infrastructure, and production-grade AI systems, collaborating with product teams and fellow researchers.

The role emphasizes prototyping, rapid iteration, and solving complex problems in real-world applications, with a strong emphasis on scalable, robust AI architectures and systems-level thinking.

Qualifikationen

• Bachelor's degree in Computer Science, a relevant technical field with a focus on AI research, or equivalent practical experience.
• 8 years of experience in the full lifecycle of research modeling.
• Experience working with two or more of the following: advanced algorithms, machine learning, information retrieval, natural language processing, data science, distributed and parallel systems, developing software systems.

Aufgaben

• Develop a wide range of solutions, spanning from modeling to infrastructure.
• Work with multiple codebases and machine learning libraries, creating throwaway models and prototypes, and reusable architectures.
• Work in the context of real applications for important Google products and collaborate with product teams and other research engineers.
• Develop novel and practical solutions for AI and AI-powered tools, moving quickly and iterating on complex problems.

Kenntnisse

Research modeling

AI/ML algorithms

Problem solving

Prototyping

Ausbildung

Bachelor's degree in Computer Science

Jobbeschreibung

Google DeepMind is seeking a Share Software Engineer focused on Generative AI to push the boundaries of AI research and engineering in Zurich. You will contribute across modeling, infrastructure, and production-grade AI systems, collaborating with product teams and fellow researchers.

The role emphasizes prototyping, rapid iteration, and solving complex problems in real-world applications, with a strong emphasis on scalable, robust AI architectures and systems-level thinking.