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Snapshot
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.
About Us
The PRISM (Planning, Reasoning, Inference & Structured models) team is an interdisciplinary, collaborative team focused on delivering fundamental advances at the edge of large-scale AI systems, with a long term goal of building agents with advanced capabilities.
We are currently focusing on developing advanced planning and reasoning capabilities for Large Language Models (Gemini).
Our team has also worked on topics including model-based RL, variational and probabilistic generative models, graph neural networks, and applications of AI to mathematics, science, and cybersecurity.
Key responsibilities:
- Understand, design, build, and maintain highly scalable and efficient ML systems and pipelines.
- Optimize existing codebases for performance, reliability, and resource utilization.
- Push the boundaries of AI by exploring new research avenues and implementing cutting-edge techniques; validating their effectiveness through comprehensive experimental testing and analysis.
- Stay abreast of the latest advancements in the field and identify opportunities to apply them.
- Provide technical guidance and mentorship to other engineers and researchers.
- Take ownership of critical issues and drive collaborative efforts to ensure project success.
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:
- Possesses a deep intellectual curiosity and a relentless drive to understand the intricacies of machine learning models and training systems.
- A true team player who prioritizes collective success. This person is flexible, collaborative, and willing to contribute wherever needed to achieve project goals, fostering a positive and supportive team environment.
- Embraces a hacker mindset, fearlessly diving into complex codebases and technical challenges. Capable of both rapid prototyping for experimentation and developing robust, production-ready code for long-term solutions.
- Programming experience in Python and machine learning libraries such as jax, tensorflow or pytorch.
- Experience implementing state of the art machine learning algorithms and understand how to analyze results using notebooks and libraries such as pandas.
- Great communication skills, able to explain ideas at the conceptual level.
In addition, the following would be an advantage:
- A degree in computer science, math or physics.
- Experience with serving and training Large Language Models.
- Knowledge of hardware acceleration of machine learning algorithms.
- Knowledge of distributed computing.
- Interest in reinforcement learning.
