Senior Research Scientist, Cloud AI Research

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

Job summary

Google is seeking a Research Scientist to conduct foundational agentic research and deploy promising ideas at scale within the Google Cloud AI Research team. You will design agent architectures, planning frameworks, and self-improving foundation models to advance autonomous AI systems across Google products and services.

You will collaborate with product and engineering teams to translate novel prototypes into scalable enterprise solutions, publish breakthroughs, and contribute to benchmarks and

Qualifications

• PhD in Computer Science, a related field, or equivalent practical experience.
• 2 years of experience developing autonomous agents, multi-agent workflows, or agentic frameworks (e.g., AutoGen, CrewAI, LangGraph, tool-use/function-calling, or multi-agent RL).
• Experience designing, pre-training, fine-tuning, or evaluating Large Language Models (LLMs) and multimodal foundation models.
• Two or more first-author scientific publication submissions on agents in ML and NLP for conferences, journals, or public repositories (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP).

Responsibilities

• Conduct foundational agentic research and develop state-of-the-art agent architectures and planning frameworks.
• Solve complex business challenges by delivering high-impact vertical agents across core domains (infrastructure, forecasting, optimization).
• Build generalizable horizontal agents to accelerate researcher velocity and automate enterprise value generation.
• Partner with product and engineering teams to translate prototypes into scalable enterprise solutions.
• Publish breakthroughs at ML conferences and establish benchmarks in collaboration across Google.

Skills

Autonomous agents

LLMs & multimodal models

Publications ML/NLP

Education

PhD in Computer Science or related field

Tools

AutoGen

CrewAI

LangGraph

Tool-use/Function-calling

Multi-agent RL

Job description

• PhD in Computer Science, a related field, or equivalent practical experience.
• 2 years of Experience developing autonomous agents, multi-agent workflows, or agentic frameworks (e.g., AutoGen, CrewAI, LangGraph, tool-use/function-calling, or multi-agent RL).
• Experience designing, pre-training, fine-tuning, or evaluating Large Language Models (LLMs) and multimodal foundation models.
• Two or more first-author scientific publication submission(s) on agents in machine learning and natural language processing for conferences, journals, or public repositories (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP).

Minimum qualifications

• PhD in Computer Science, a related field, or equivalent practical experience.
• 2 years of Experience developing autonomous agents, multi-agent workflows, or agentic frameworks (e.g., AutoGen, CrewAI, LangGraph, tool-use/function-calling, or multi-agent RL).
• Experience designing, pre-training, fine-tuning, or evaluating Large Language Models (LLMs) and multimodal foundation models.
• Two or more first-author scientific publication submission(s) on agents in machine learning and natural language processing for conferences, journals, or public repositories (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP).

Preferred qualifications

• Experience building evaluation benchmarks, test harnesses, or simulation environments for complex reasoning, code generation, or multimodal tasks.
• Experience in RL, reward modeling, and human/AI preference alignment techniques (e.g., RLHF, RLAIF, DPO).
• Experience developing test-time/inference-time compute scaling methods, search-guided decoding, or planning algorithms.
• Experience developing safe and reliable AI systems, including adversarial robustness, hallucination mitigation, alignment guardrails, model interpretability.

About The Job

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.

The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.

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

Responsibilities

Learn more about benefits at Google .

• Conduct foundational agentic research, develop state-of-the-art agent architectures, planning frameworks, and self-improving foundation models to advance autonomous AI systems.
• Solve complex business challenges, design and deliver high-impact vertical agents across core domains (e.g., infrastructure, forecasting, and optimization) targeting operational efficiencies.
• Build generalizable horizontal agents to accelerate researcher velocity and automate end-to-end business value generation across Google.
• Partner with product and engineering teams to translate novel agentic prototypes into scalable enterprise solutions and products.
• Advance the scientific community, publish breakthroughs at the ML conferences, establish benchmarks, and collaborate across Google.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .