Opening. We are looking for a Research Engineer to lead our efforts in developing and scaling novel algorithmic methods that push the frontier of AI and its applications.
What you'll do
As a Research Engineer at Google DeepMind, you will design, implement, scale and evaluate state-of-the-art deep learning models (e.g., Transformers, GNNs) and software prototypes for sustainability-related problems.
- Design, implement, scale and evaluate state-of-the-art deep learning models (e.g., Transformers, GNNs) and software prototypes for sustainability-related problems.
- Build robust and scalable data processing and training pipelines to enable rapid research iterations.
- Report and present findings and developments clearly and efficiently, both internally and externally.
- Contribute to team collaborations to meet ambitious research and product goals.
- Engage with application and product needs, to inform research and engineering decisions.
What you need
- BSc, MSc or PhD/DPhil degree in computer science, mathematics, applied stats, machine learning or equivalent practical experience.
- Strong background in deep learning, with proven experience with relevant architectures (e.g., Transformers, GNNs, etc).
- Strong background in machine learning foundations (esp. supervised learning, probabilistic modeling, graph-based learning, and/or optimization).
- Excellent software engineering skills with a proven ability to build robust and scalable systems.
- Proficiency in deep learning frameworks like JAX, TensorFlow, or PyTorch is essential.
- Experience with either large-scale data processing frameworks (e.g., Apache Beam, Spark) or distributed training infrastructure.
