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.
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
- Excellent software engineering skills in Python, Go, or Rust.
- Extensive experience designing, building, and maintaining modular and reusable systems.
- Experience collaborating with engineers and researchers to understand complex requirements and deliver clear solutions.
- Ability to implement large-impact changes across the organization with minimal disruption.
- Experience building internal tooling for AI research and development workflows (debugging, evaluation, experiment tracking/versioning, CI automation).
What We Do
Genesis AI is a global full-stack robotics company developing general-purpose robots with human-level intelligence and capabilities. It aims to build foundational AI models that automate repetitive tasks across applications such as lab work and housekeeping. The company uses a proprietary physics engine to generate synthetic physical-world data, helping train robotics models for diverse real-world environments, and operates across Paris and Silicon Valley.
