Genesis AI

Genesis AI provides a simulation-driven platform and full-stack robotics to accelerate training and deployment of general-purpose robots. It combines generative simulation, reinforcement-learning…

genesis-ai.company

Genesis AI

Genesis AI provides a simulation-driven platform and full-stack robotics to accelerate training and deployment of general-purpose robots. It combines generative simulation, reinforcement-learning…

genesis-ai.company

HQParis, FR

Team Size73

Open JobsUnknown

Total Funding$105M

Latest Fundraise12 months ago

Join the Team

Member of Technical Staff, Platform (Bay Area, Remote)

On-SiteLondon Area, GB

On-Site • London Area, GB

What You'll Do

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Mobile Developer

Part-timeManchester, GB

Part-time • Manchester, GB

DevOps Engineer

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Contract • Haifa

Machine Learning Engineer

Part-timeRotterdam, NL

Part-time • Rotterdam, NL

Backend Developer

Part-timeAmsterdam, NL

Part-time • Amsterdam, NL

Technical Writer

InternshipNiš, RS

Internship • Niš, RS

Product Designer

Part-timeBerlin, DE

Part-time • Berlin, DE

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.).