Staff Research, Generative Ai, Cloud AI Research, Co-scientist

Google Google · Big Tech · Zürich, Switzerland

Staff Research Software Engineer to lead the design and implementation of multi-agent reasoning models for the Co-Scientist system, an autonomous virtual scientific colleague built on Gemini. The role involves architecting and deploying agentic AI systems, coordinating multi-agent prompting, and establishing robust evaluation pipelines to accelerate scientific discovery.

What you'd actually do

  1. Own projects end-to-end, leading teams from initial scientific research concepts through software design, testing, deployment, and performance analysis.
  2. Architect, build, and deploy agentic AI systems, coordinating multi-agent prompting techniques and asynchronous task execution frameworks.
  3. Drive technical decisions, sound architectural choices, and full-stack software development using Python, C++, and Google's core backend components.
  4. Design and establish robust evaluation pipelines, automated test suites, and diagnostic datasets to measure agent performance under extreme scale.
  5. Drive collaborative research with Google DeepMind, Google Research, and university labs to solve complex, open-ended scientific problems. Provide technical leadership, mentor junior engineers, and advocate engineering quality across the organisation.

Skills

Required

  • software development
  • software design and architecture
  • ML design
  • ML infrastructure optimization
  • GenAI techniques
  • LLMs
  • Multi-Modal
  • Large Vision Models
  • language modeling
  • computer vision
  • Python
  • C++

Nice to have

  • PhD or Postdoc in Computer Science, Applied Math, Computational Sciences, or a related scientific discipline
  • paper authorship
  • deep learning frameworks
  • JAX
  • TensorFlow
  • PyTorch
  • algorithmic background
  • technical leadership role
  • independent, research-adjacent software development
  • translate academic theories into concrete, scalable products
  • technical or scientific contributions to complex, large-scale projects

What the JD emphasized

  • lead the design and implementation of highly multi-agent reasoning models
  • architect, build, and deploy agentic AI systems
  • robust evaluation pipelines

Other signals

  • multi-agent reasoning models
  • Co-Scientist is a multi-agent AI system built on Gemini
  • autonomous virtual scientific colleague
  • generate, debate, and evolve
  • accelerate scientific discovery
  • synthesize literature, evaluate hypotheses, and optimize experimental designs
  • architect, build, and deploy agentic AI systems
  • coordinating multi-agent prompting techniques and asynchronous task execution frameworks
  • design and establish robust evaluation pipelines, automated test suites, and diagnostic datasets to measure agent performance under extreme scale