About the Role
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re 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. We are seeking a Research Engineer to join our team dedicated to AI for Healthcare. In this role, you will engage in cutting-edge research into vital technologies underpinning next-generation models while simultaneously contributing to the exploration of various applications. We are seeking a highly motivated Research Engineer with expertise in deep learning, distributed computing and data pipelines. You will collaborate globally with research scientists and software engineers to build, evaluate, and deploy state-of-the-art AI models for healthcare. In this role, you will develop the robust data, evaluation, and inference pipelines that drive our research, alongside creating rigorously designed evaluation datasets. Beyond this foundational work, you will adapt model architectures and drive the real-world validation of these systems. At Google DeepMind, you will tackle fundamental challenges in machine learning, turning cutting-edge research into tangible, real-world impact.
Responsibilities
- Develop and establish pipelines to make our work more scalable and efficient.
- Develop and establish benchmarks for evaluating language & multimodal models across a wide range of tasks and domains.
- Contribute effectively within a collaborative environment to achieve ambitious research goals.
Requirements
- A proven track record in deep learning (demonstrated via publications, open-source projects, relevant work experience, etc.).
- Experience managing compute resources (GPUs/TPUs), data pipelines, and the platforms used to train, evaluate, and scale complex AI/ML models.
- The ability to communicate technical ideas effectively.
Qualifications
Hands-on experience tackling the engineering complexities of agentic systems and infrastructure is a plus.