The role
From Google's own posting.
As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google .
Make core contributions to Gemini that advance what digital agents can do and are deployable into production.
Identify model areas of improvement.
Train and evaluate agents across various digital environments.
Focus on multi-step reinforcement learning in multimodal, digital environments.
Minimum qualifications:
PhD degree in Computer Science, Artificial Intelligence, a related field, or equivalent practical experience.
2 years of experience in developing and training machine learning models
Experience developing and deploying models using deep learning frameworks (e.g., TensorFlow, PyTorch, or JAX).
Experience with Large Language Models, NLP, or Generative AI.
Experience in Python programming.
Preferred qualifications:
PhD degree in Computer Science or a related field.
Experience in Generative AI.
Deep expertise in reinforcement learning.
PhD degree in Computer Science, Artificial Intelligence, a related field, or equivalent practical experience.
2 years of experience in developing and training machine learning models
Experience developing and deploying models using deep learning frameworks (e.g., TensorFlow, PyTorch, or JAX).
Experience with Large Language Models, NLP, or Generative AI.
Experience in Python programming.