Research Engineer, Advancing Agent Quality, DeepMind

Google Inc.; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google DeepMind in Mountain View, CA is seeking a Research Engineer, Advancing Agent Quality to join the Agent Quality team. You will help define evaluation systems, build agent environments, and support Gemini Spark with scalable experiments.

This role emphasizes hands-on development in ML and software engineering, with Python and major frameworks, contributing to long-horizon tool-using capabilities and high-quality research outputs for global collaboration.

Qualifications

• 2+ years in agentic AI workflows and frameworks.
• 1+ year in machine learning and deep learning.
• Experience in software engineering and cloud-based development.
• Proficient with Python and ML frameworks (TensorFlow, PyTorch).

Responsibilities

• Design, build, and scale agent environments and test suites.
• Research and develop Agentic AutoRaters calibrated to human evaluation.
• Develop trajectory analysis tools to identify failure modes and improve data harnesses.
• Harvest trajectories and rewards for SFT and RL training of Gemini models.

Skills

Agentic AI workflows

Machine learning

Software engineering

Cloud development

Python

TensorFlow

PyTorch

Job description

Research Engineer, Advancing Agent Quality, DeepMind

Share Research Engineer, Advancing Agent Quality, DeepMind

corporate_fare DeepMind place Mountain View, CA, USA

• 2 years of experience with agentic AI workflows, frameworks, and approaches.
• 1 year of experience with machine learning and deep learning.
• Experienece in software engineering and cloud-based development.
• Experience with Python, TensorFlow, PyTorch, or similar ML frameworks.

Preferred qualifications:

• In-depth knowledge of machine learning algorithms, including supervised learning and reinforcement learning.

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.

The Agent Quality team defines, measures, and advances long-horizon, tool-using capabilities for Google’s frontier agents. We build foundational evaluation systems and data flywheels for Gemini Spark—Google’s flagship agent for deep research, multi-step problem solving, and workspace integration. Our work encompasses pioneering environment creation (including contexts, autoraters, human evaluations), developing advanced diagnostic tools for agent improvement, and harvesting trajectories and reward signals into SFT and RL post-training to recursively improve core Gemini models.

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.

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.

The Agent Quality team defines, measures, and advances long-horizon, tool-using capabilities for Google’s frontier agents. We build foundational evaluation systems and data flywheels for Gemini Spark—Google’s flagship agent for deep research, multi-step problem solving, and workspace integration. Our work encompasses pioneering environment creation (including contexts, autoraters, human evaluations), developing advanced diagnostic tools for agent improvement, and harvesting trajectories and reward signals into SFT and RL post-training to recursively improve core Gemini models.

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

• Design, build, and scale realistic agent environments and task suites. Research and develop Agentic AutoRaters (AR), calibrate them against human evaluation, and benchmark agent capabilities against industry-leading frontier models.
• Enable agents to automatically generate and iterate on verifiers (such as automated test cases), facilitating effective exploration and iterative problem-solving.
• Develop trajectory analysis frameworks and diagnostic tooling to identify root-cause agent failure modes (e.g., passivity, hallucination, or brittle tool execution), and automatically optimize agent harnesses to drive continuous self-improvement.
• Harvest complex multi-turn interaction trajectories into high-quality datasets and reward signals to power SFT and RL flywheels for frontier Gemini models.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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.