
Research Engineer, Google DeepMind Impact Accelerator
2 days ago
Job Description
The Google DeepMind Impact Accelerator (GDI) has a unique role in GDM, to develop solutions and resources built on GDM's technologies and expertise that extend their benefits to humanity. We are a path to real world impact, beyond Google products and services or making our research public. For example, GDI is the team behind the public version of AlphaFold available to anyone for non-commercial use at
In this role, you will be at the forefront of bringing Google DeepMind's cutting-edge AI research to the world. You'll work directly with researchers, engineers, product managers and others to deploy AI models onto Google's production infrastructure, impacting society and the world in positive ways. This involves a blend of technical expertise and collaborative problem-solving to ensure both efficiency and quality throughout the entire deployment lifecycle.
Job responsibilities
- Solving key research challenges, via designing and running experiments, sharing analyses and proposing next steps.
- Adapting and enabling use of key research technologies for specific applications and partnerships.
- Develop, maintain, and extend AI deployment solutions in response to user feedback and strategic priorities, for example web services, open source software, and data access solutions.
- Develop expertise in ML deployment using Google's tech stack and bringing this into research projects and products. Sharing your skills and knowledge with other engineers and researchers.
- Stay informed on relevant industry trends and internal research developments.
Minimum qualifications
- Bachelor's degree in computer science, electrical engineering, science, mathematics or equivalent practical experience.
- 2 years of experience with software development in programming languages such as C++ and/or Python.
- Experience with Python-based scientific libraries such as JAX, PyTorch, TensorFlow, NumPy.
- Experience with deploying ML or AI systems.
Preferred qualifications
- Experience delivering ML-driven solutions in areas relevant to GDI, such as food security, global health, and energy systems.
- Academic research/publications experience in machine learning or related fields.
- Experience with HTML, JavaScript, TypeScript, Angular.
- Familiarity with modern hardware accelerators (e.g., GPU / TPU).
TensorFlow
Experiment design
Web Services
Software development process
Software Engineering
Computer Science
PyTorch
Python
Experimental techniques
Research
Software Development
C++
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