Research Engineer, Multimodal and Video Modeling

At Google DeepMind we value diversity of experience knowledge backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex race religion or belief ethnic or national origin disability age citizenship marital domestic or civil partnership status sexual orientation gender identity pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation please do not hesitate to let us know.

Snapshot

Artificial Intelligence could be one of humanitys most useful inventions. At Google DeepMind were a team of scientists engineers machine learning experts and more working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery and collaborate with others on critical challenges ensuring safety and ethics are the highest priority.

The Role

Were looking for a Research Engineer with exceptional programming and engineering skills a deep understanding of large-scale neural network training and data processing and a strong working knowledge of machine learning experimentation. The ideal candidate will have hands-on experience with training and developing multimodal models.

Key responsibilities:

• Develop maintain and improve large-scale multimodal models with a focus on video modeling and the data pipelines for training and evaluation.
• Design and implement novel methods for evaluating and improving multi-modal generative models particularly at the post-training stage.
• Build and maintain robust data pipelines for collecting and processing large-scale datasets including human-labeled data.
• Collaborate with research scientists to translate research ideas into production-ready code.

About You

In order to set you up for success as a Research Engineer at Google DeepMind we look for the following skills and experience:

• BSc MSc or PhD/DPhil degree in computer science physics mathematics applied statistics machine learning or equivalent practical experience.
• Strong background in deep learning with proven experience with relevant architectures (e.g. Transformers GNNs etc).
• Experience with training large-scale machine learning models particularly in the multimodal domain (video text).
• Excellent software engineering skills with a proven ability to build robust and scalable systems.
• Proficiency with ML and scientific libraries such as JAX TensorFlow PyTorch NumPy and Pandas.
• Experience with either large-scale data processing frameworks (e.g. Apache Beam Spark) or distributed training infrastructure.

In addition the following would be an advantage:

• Experience with LLMs VLMs and/or diffusion models training and inference.
• Experience with Computer Vision tasks (video classification object tracking depth estimation etc.)
• Experience working in a team on projects from the initial proof-of-concept stage to final implementation and evaluation.