What are the responsibilities and job description for the Research Engineer, Gemini Latent Thinking, DeepMind position at Google DeepMind?
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Cambridge, MA, USA; Mountain View, CA, USA.Minimum qualifications:
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.
The US base salary range for this full-time position is $207,000-$300,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
Responsibilities
- Bachelor’s degree in Computer Science, Statistics, Machine Learning, a related technical field, or equivalent practical experience.
- 8 years of experience in software development.
- One or more scientific publications with citations, or public repositories with stars/forks.
- Experience in Large Language Model (LLM) training (pre-training or post-training).
- Experience publishing in conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR).
- Ability to formulate research hypotheses and design experiments to validate results.
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.
The US base salary range for this full-time position is $207,000-$300,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
Responsibilities
- Architect, scale, and land latent thinking with us.
- Develop novel algorithms for Large Language Models (LLMs) and reasoning.
- Formulate sound research hypotheses.
- Design, implement, and perform ML experiments (including ablations) to validate the research hypotheses.
- Partner with research and engineering teams to land scientific breakthroughs into frontier models.