AI Trainer: Code Generation

Role Summary

We are building a focused group of engineers to improve how large language models reason through real world code. This initiative centers on evaluating and refining multi step reasoning trajectories derived from real GitHub repositories, with the goal of producing higher quality, more reliable code generation outputs.

This is a long term project requiring strong engineering judgment rather than surface level labeling. Contributors will work directly with complex code paths and reasoning flows across multiple platforms.

This includes

• Reviewing model generated reasoning sequences
• Identifying logical inconsistencies or weak reasoning steps
• Improving trajectory structure to produce stronger, production grade outputs
• Evaluating reasoning quality across different programming environments

The work is closer to debugging model logic and reasoning systems than to traditional annotation tasks.

Responsibilities

You will analyze and refine multi step code reasoning trajectories generated from real production repositories.

Requirements

We are looking for engineers with strong hands on development experience and deep familiarity with real codebases.

You should

• Be proficient in at least two mainstream programming languages such as Python, C++, Java, TypeScript, or JavaScript
• Have real world development experience in areas such as backend systems, frontend applications, algorithms, testing, or infrastructure
• Be comfortable reading and reasoning through large GitHub repositories
• Have strong written communication skills

Experience contributing to high visibility or high star GitHub repositories is a strong plus.

ADDITIONAL DETAILS

We expect to onboard approximately 10 to 20 engineers for this long term initiative. A short qualification exercise may be required prior to joining.

About the Company

ABOUT MOONLAKE

Moonlake is building the frontier of interactive world models: systems that generate, simulate, and reason over 3D environments for embodied AI, robotics and gaming. We develop the simulation infrastructure to build worlds (e.g., assets, scenes, digital twins) at scale.

Our team sits at the intersection of

Moonlake is building the next generation of AI infrastructure for interactive digital worlds. Our mission is to enable anyone to create, simulate, and interact with rich environments using natural language and multimodal inputs, turning simple ideas into worlds with structure, logic, and agents that can perceive and act.

Our team has raised $28M in seed funding from NVIDIA Ventures, Threshold Ventures, AIX ventures and notable angels including Naval Ravikant and Jeff Dean to build the foundational layer for the future of AI - powering everything from creative tools and games to robotics training, simulations, and digital twins. Our goal is to make building and experimenting with these environments as accessible and scalable as publishing video on the internet.

We are looking for exceptional research engineers and applied researchers to help push the frontier of interactive AI.

Embodied AI

Robotics simulation

Interactive 3D worlds

World models

Real-time generation

AI infrastructure