Research Engineer, Gemini Information Task, DeepMind

Google; United States; On-site; USD 174,000 - 252,000; Full time

Benefits offered by this job

Equity

Bonus target

Job summary

Google DeepMind is seeking a Research Engineer for the Gemini Information Task to advance state-of-the-art information retrieval and AI-powered reasoning capabilities. You will design experiments, build scalable systems, and collaborate with cross-disciplinary teams to push research into production.

The role emphasizes strong ML foundations, software engineering in Python and C++, and experience with JAX or PyTorch. Expect impactful work across large-scale data, models, and product integrations.

Qualifications

• Bachelor's degree or equivalent practical experience in CS or a related technical field.
• 3 years of experience in machine learning with focus on LLMs or information retrieval.
• 3 years of software engineering with Python, C++, JAX or PyTorch, including multi-stage training pipelines.

Responsibilities

• Uncover strategic opportunities at Gemini, Search, factuality, continual learning and deep research.
• Analyze models and model-driven products beyond current leaderboards and measure ideal behavior.
• Develop practical interventions and modeling innovations to improve models across surfaces.
• Collaborate with product teams like Search and YouTube to scale research into production.

Skills

Machine Learning

Python

C++

JAX/PyTorch

Education

Bachelor's degree in CS/related field

Tools

JAX

PyTorch

Python

Job description

Research Engineer, Gemini Information Task, DeepMind

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Francisco, CA, USA.

Minimum qualifications:

• Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related technical field, or equivalent practical experience.
• 3 years of experience in machine learning, with a focus on Large Language Models (LLMs) or Information Retrieval (IR).
• 3 years of experience with software engineering in Python, C++, JAX, or PyTorch programming, including experience implementing multi-stage training pipelines or algorithms.

Preferred qualifications:

• Experience developing Reinforcement Learning (RL) algorithms, automated evaluation systems, or LLM reflection and reasoning frameworks.
• Experience with competitive programming, mathematics competitions (e.g., ICPC, IOI, IMO), or a track record of developing novel algorithms.
• Experience rapidly prototyping and iterating on complex systems, generative AI models, or multi-stage pipelines.
• Experience collaborating with product engineering teams to deploy machine learning models or research innovations into large-scale production environments (e.g., Search, Recommendation Systems).
• Track record of learning new software tools, frameworks, and codebases quickly to solve complex technical obstacles.

About the job

At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.

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.

Responsibilities

• Uncover strategic opportunities at the intersection of Gemini, Search, factuality, continual learning, deep research, and domain internalization.
• Analyze models and model-driven products beyond current leaderboards—understand complex problem spaces and create new ways to measure ideal behavior.
• Use empirical findings to develop practical interventions and modeling innovations to improve our models across downstream surfaces.
• Collaborate with product teams like Search and YouTube to scale research innovations into production environments, optimizing for quality and efficiency.

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Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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