Google

Research Scientist, Cloud AI Research

Google$147K — $210K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in Computer Science or related field, or equivalent practical experience.
  • Experience with autonomous agents and multi-agent workflows.
  • Proven track record in designing and evaluating Large Language Models and multimodal foundation models.
  • Strong coding skills in Python, JavaScript, R, Java, or C.
  • First-author publications on agents in machine learning and natural language processing.

Responsibilities

  • Develop innovative agent architectures and self-improving models.
  • Design agents targeting various operational efficiencies, such as infrastructure and forecasting.
  • Create generalizable agents to boost research productivity and automate business functions.
  • Collaborate with product and engineering teams to create scalable AI solutions.
  • Publish research breakthroughs and set benchmarks in the AI field.

Benefits

  • Generous equity options.
  • 15% bonus target.
  • Comprehensive health coverage.
  • Employee wellness programs.
  • Flexible work arrangements.
Full Job Description
Minimum qualifications:
  • PhD in Computer Science, a related field, or equivalent practical experience.
  • 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.
  • Experience writing code in Python, JavaScript, R, Java, or C .
  • One 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, hallucination mitigation, alignment guardrails, model interpretability.


Responsibilities
  • Develop agent architectures, planning frameworks, and self-improving foundation models to advance autonomous AI systems.
  • Design and deliver 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.
  • Publish breakthroughs at ML conferences, establish benchmarks, and collaborate across Google.


US: $147000 - $210000 (USD) 15% bonus target equity benefits

Learn more about benefits at Google .

About Google

Google is a multinational technology company that specializes in Internet-related services and products. These include online advertising technologies, search engine, cloud computing, software, and hardware. Google was founded in 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University. The company has grown tremendously since then and has become one of the most valuable companies in the world. Google's mission is to organize the world's information and make it universally accessible and useful.
Learn more about Google
Size
156,500 employees
Market Cap
$1,115.4 billion
Industry
Net Income
$40.2 billion
Founded
1998
5 Year Trend
+23.3%
Revenue
$182.5 billion
NASDAQ

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