Research Engineer: Generative AI & Diffusion Models

Job-Room; Zürich; Hybrid; CHF 180.000 - 260.000; Vollzeit

Zusammenfassung

Google DeepMind is seeking research-focused Software Engineers who will embed across teams to prototype, train and deploy large-scale AI models. You will work on generative media, multimodal understanding and optimized inference in real-world problems, alongside academia and industry collaborations.

The role emphasizes publishing, collaboration with universities, and advancing AI safety and ethics while delivering high-impact innovations for billions of users.

Qualifikationen

• Master's degree in computer science, mathematics, applied statistics, machine learning or equivalent practical experience.
• Experience with TensorFlow or ML frameworks (e.g. JAX or PyTorch).
• Experience working in industry, working on projects from proof-of-concept through to implementation.
• Experience with training diffusion models.
• Experience conducting applied research.

Aufgaben

• Apply research ideas to high-impact real world problems through prototyping, dataset curation, model training, performance optimization, and deployment.
• Develop cutting-edge techniques in Generative Media (image, video, and audio).
• Optimize algorithms and models for efficient inference.
• Advance capabilities in Multimodal Understanding.
• Perform comprehensive model optimization to enhance performance and scale.

Kenntnisse

Applied research

Cross-functional collaboration

ML theory

Diffusion models

Inf. optimization

Data pipelines

Large-scale models

Industry experience

Ausbildung

Master's degree in computer science/mathematics/applied statistics/machine learning

Tools

TensorFlow

JAX

PyTorch

Jobbeschreibung

Google DeepMind is seeking research-focused Software Engineers who will embed across teams to prototype, train and deploy large-scale AI models. You will work on generative media, multimodal understanding and optimized inference in real-world problems, alongside academia and industry collaborations.

The role emphasizes publishing, collaboration with universities, and advancing AI safety and ethics while delivering high-impact innovations for billions of users.