Research Engineer, Polaris, DeepMind

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.
Engineers on the Polaris team design tasks that test Gemini’s ability to complete software engineering work. A task is essentially an in-depth examination that evaluates how well Gemini performs in a specific, complex scenario. The primary components of a task are: a prompt that instructs Gemini what to do and a grader or rubric that assigns a numerical score to the model’s attempted solution.
Our team, Polaris, is distinguished primarily by how much manual effort we put into building individual tasks. Rather than generating a large number of tasks using a synthetic data pipeline, engineers on the Polaris team prioritize creating a smaller number of tasks that more closely capture the realism and complexity of real-world software engineering. A single well-designed task typically takes a Polaris engineer roughly one week to complete, from the initial ideation stage to final approval.
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.
Base Salary Range:
$164,000 - $252,000 (USD)
Total Compensation Range: $550,000 – $1,100,000 (inclusive of 15% target annual bonus, equity and sign-on bonus)
Learn more about
benefits at Google
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Minimum qualifications
Experience in software development or programming.
Experience using AI-assisted coding tools, developer agents, or LLM-based workflows for software development.
Experience using coding agents for performing work.

Preferred qualifications
Experience participating in competitive programming, mathematics competitions (e.g., IMO, USAMO, Putnam, or IOI), or hackathons.
Experience designing rubrics, evaluation frameworks, or benchmark datasets for machine learning models.
Demonstrated ability to quickly adapt to and learn new programming paradigms, tools, and technical stacks.

Responsibilities
Create tasks that will be used to measure Gemini’s ability to perform long-horizon software engineering tasks, and launch entirely new projects within DeepMind aimed at improving Gemini’s training data and evaluations (evals).