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GOGoogle DeepMind

Research Engineer, Multimodal Reinforcement Learning(m/w/x)

Zürich
Full-timeOn-siteExperienced
AI/ML

Building infrastructure for autoraters and multi-turn reasoning environments at a global AI research lab. PhD in Computer Science or equivalent research track record required. Access to world-class compute and scientific publishing opportunities.

Requirements

  • Technical proficiency and curiosity about learning mechanics
  • Knowledge of latest Reinforcement Learning methods
  • Ability to bridge research and implementation
  • PhD in Computer Science, AI, or equivalent practical experience
  • Proven research track record and scientific contributions
  • Experience with multimodal models and visual grounding
  • Strong coding skills and complex experiment execution
  • Experience with RAG, embeddings, or search infrastructure
  • Familiarity with multi-agent negotiation frameworks
  • Experience building training environments or reward models

Tasks

  • Design and implement novel RL algorithms
  • Enable multi-turn reasoning in multimodal environments
  • Build infrastructure for autoraters and autousers
  • Generate high-quality, semi-verifiable training environments at scale
  • Apply state-of-the-art methods to strategic problems
  • Close the gap between single-turn and multi-turn embeddings
  • Track, interpret, and analyze complex experiments
  • Provide scientific rigor to training pipelines
  • Collaborate across Google Research, Core, and GDM GenAI teams
  • Build shared pipelines for conversational infrastructure
  • Support product needs in Search, Lens, and YouTube

Work Experience

approx. 1 - 4 years

Education

Doctoral / PhD

Languages

EnglishBusiness Fluent

Tools & Technologies

PythonJAXTensorFlowPyTorchRAG

Benefits

Learning & Development

  • Scientific publishing opportunities

Modern Equipment

  • Access to world-class compute

Other Benefits

  • Existing infrastructure access

Startup Environment

  • Supportive, growth-oriented environment
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