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Genesis· Engineering & Research
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Hybrid (Paris), Hybrid (London)Full-timePosted 5mo ago

About the role

Design, build, and maintain foundational frameworks and tools to empower expert teams to experiment fast and turn ideas into production-ready systems; collaborate across teams to validate use cases and create modular, reusable components; improve design quality and workflow efficiency; promote good practices through reviews, documentation, and training.

Responsibilities

  • Design, build, and maintain foundational frameworks and tools to empower expert teams to experiment fast and turn ideas into full-fledged and production-ready systems.
  • Collaborate with expert teams to validate uses cases and build robust solutions, bringing cross-team perspective and aiming for modular and reusable components.
  • Identify and mitigate high-level code design flaws and development workflow inefficiencies that cause friction, hinder productivity, and create silos across the organization.
  • Advocate for good practices and maintain high code quality through code reviews, documentation, and training.

Qualifications

  • Excellent software engineering skills (e.g., in Python, Go, or Rust).
  • Extensive experience designing, building, and maintaining modular and reusable systems.
  • Experience collaborating with engineers and researchers of any fields, understanding complex requirements, and providing clear and simple solutions.
  • Ability to implement large-impact changes across the organization with minimal disruption.
  • Experience building internal tooling to accelerate AI research and development workflows (e.g., debugging, evaluation, experiment tracking and versioning, CI automation, etc.).

Skills

Required:Software engineeringModular system designCross-functional collaboration
Nice to have:Internal tooling for AI workflows
Last updated Jul 16, 2026. Interested? Apply on the company site.

About Genesis

A new future is at hand.

We are a new generation of robotics builders, united by a shared mission to push the boundaries of physical AI.

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