---
title: 'Member of Technical Staff — Agent Post-Training at Moonlake'
canonical: 'https://feeny.ai/job/member-of-technical-staff-agent-post-training-moonlake-san-francisco-gk4mq3zztbe9'
type: 'job'
last_seen: '2026-09-13'
---

# Member of Technical Staff — Agent Post-Training at Moonlake

- **Company:** Moonlake
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Posted:** 2026-07-28
- **Last confirmed live:** 2026-09-13
- **Apply:** https://jobs.ashbyhq.com/moonlake/3be365f1-075b-463e-b352-b81888c62f55

## Job description

Introducing Moonlake, AI for creating world simulations.

## About Moonlake

Moonlake is building the frontier of interactive world models: systems that generate, simulate, and reason over 3D environments for robotics, embodied AI, and interactive applications. We develop the infrastructure that enables intelligent systems to learn, evaluate, and interact within realistic virtual environments before operating in the physical world. Our work sits at the intersection of:

- Robotics
- Embodied AI
- Interactive 3D Worlds
- World Models
- Simulation Infrastructure
- Physical AI

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, physics, and intelligent behavior. Our team has raised $50M 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 robotics training and simulation to digital twins and interactive environments. We are looking for exceptional engineers to help build the simulation systems that will power the next generation of robotics and embodied intelligence.

## The Role

We are hiring a Member of Technical Staff to lead reinforcement learning infrastructure and model post-training. You will work closely with Qi and the research team to improve large vision-language and code-generating agents through fine-tuning, reinforcement learning, trajectory data, and scalable evaluation. Moonlake already has deep expertise in 3D and world-building. This role adds the model-training experience needed to systematically improve agent performance and prepare the company for larger-scale RL across both digital and physical environments. We are looking for a full-stack researcher and engineer who understands the complete training system and can make strong judgments about when training is necessary, which methods are likely to work, and what not to pursue.

## What You’ll Do

- Build RL and post-training pipelines for multimodal, vision-language, and code-generating agents
- Develop infrastructure for supervised fine-tuning, preference optimization, reward modeling, and reinforcement learning
- Create systems for collecting, filtering, replaying, and learning from agent trajectories
- Design rewards, verifiers, and evaluations for long-horizon agent tasks
- Improve agents’ ability to plan, write and execute code, use tools, recover from errors, and complete complex workflows
- Scale distributed training and high-throughput rollout generation across multi-GPU environments
- Improve training reliability, reproducibility, observability, and cost efficiency
- Help define Moonlake’s long-term strategy for agent, robotics, and embodied-model training

## What We’re Looking For

- Real-world experience training large language, vision-language, multimodal, or code models
- Strong experience in reinforcement learning, post-training, or large-scale fine-tuning
- Experience building distributed training or high-throughput inference systems
- Familiarity with supervised fine-tuning, preference optimization, reward modeling, and agentic RL
- Experience with code-generation agents, long-horizon evaluation, or tool-using systems
- Strong Python skills and experience with PyTorch, JAX, or similar frameworks
- Ability to work across data, models, environments, rewards, evaluation, and infrastructure
- Strong research judgment and a bias toward building reliable systems

## Preferred Experience

- Experience at a frontier AI lab or organization operating large-scale training systems
- Experience with code-model post-training or autonomous coding agents
- Experience with multimodal models, robotics, simulation, or embodied AI
- Experience designing verifiable rewards or outcome-based training systems
- Experience scaling RL workloads across large GPU clusters

What Success Looks Like Within your first year, you will have:

- Built Moonlake’s core post-training and RL infrastructure
- Created scalable systems for learning from agent trajectories
- Delivered measurable improvements in agent quality and task completion
- Helped the team determine which problems require training and which do not
- Established a reliable foundation for larger-scale agent and embodied-model training

## Why This Role Matters

Moonlake’s agents must do more than generate content. They must understand complex requests, reason across vision and language, write and execute code, operate tools, build interactive worlds, and recover from mistakes. This role will build the training systems that allow those agents to continuously improve.

We are committed to being an on-site, in-person team currently based in San Francisco.

## About Moonlake

## Company Overview
- **One-liner**: Moonlake AI builds multimodal world models and simulation environments to accelerate the development of physical AI and embodied intelligence.
- **Entity Type**: Private (Seed stage) – raised $28M in Seed funding
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2025
- **Founders**: Sharon Lee (Co-Founder); key team includes Yitong Deng (Founding Research Scientist) and Siddharth Ahuja (Head of Product)

## Core Business
- **Primary industry**: AI research and world modeling, with a focus on simulation for robotics, autonomous driving, and embodied AI.
- **Target customers**: B2B – enterprises in robotics, autonomous mobility, and AI research labs (e.g., OpenAI, Waymo, Stanford).
- **Mission**: “Build the frontier of sim-ready worlds and embodied AI” – enabling efficient reinforcement learning and evaluation through generative simulation environments.

## Products & Services
- **Moonlake World Model**: A real-time neural rendering model grounded in 3D information that creates high-fidelity simulation environments from text, images, point clouds, or Gaussian splats. Includes articulation, physics, and deformable objects.
- **3D Agent**: An AI agent that operates inside Blender, automating the creation of articulated assets, physics-validated scenes, and complex environments while preserving fine-grained editability.
- **Reconstruction & Agent Capabilities**: Multimodal world models that maintain state, predict outcomes, and enable planning over limited action spaces.

## Market Standing
- **Valuation / Market Cap**: Not disclosed
- **Key Metric**: Total funding of $28M (Seed round, November 2025)
- **Notable Investors**: Threshold Ventures (formerly DFJ), AIX Ventures, NVentures (NVIDIA’s venture arm). Angel investors include Jeff Dean, Ian Goodfellow, Naval Ravikant, Steve Chen, Guillermo Rauch, and Jared Leto.
- **Growth Signals**: Named to CB Insights AI 100 list (May 2026); trusted by companies with a combined market cap of $8T+ (including OpenAI, Stanford, Waymo); 4,372 LinkedIn followers (+8.2% monthly growth); small team of 15 employees with strong talent from Berkeley AI Research, Stanford, Google, and others.

## Competitive Advantages
- **Real-time 3D world model** with minimal sim-to-real gap, grounded in 3D geometry rather than purely 2D video.
- **Integration with Blender** allows artists and engineers to edit and refine generated assets interactively.
- **Multimodal state maintenance** enables world models that can simulate complex physics and deformable objects, critical for RL training.
- **Strong investor backing** from NVIDIA, top AI researchers, and unicorn founders provides strategic leverage.

## Strategic Focus
- Building a **product-driven data flywheel** – starting with tools that make simulation creation accessible to everyone, then using generated data to train better world models.
- Targeting **embodied general intelligence** by enabling massive-scale RL training and evaluation in generative worlds.
- Expanding the **“3D Agent”** to act as a technical artist, continuously refining simulations over thousands of steps.

## Why Work Here
- **Culture**: Small, high-impact research team at the frontier of world modeling and embodied AI. Team members come from top labs (Berkeley, Stanford, Google, DeepMind).
- **Location**: Headquarters in San Francisco (hybrid likely, but not explicitly stated).
- **Perks & Environment**: Not detailed, but the company emphasizes “building meaning” and a product-driven approach. Opportunities for deep technical work in neural rendering, physics simulation, and RL.
- **Recent Recognition**: CB Insights AI 100 list adds external validation and visibility.

## Sources
1. [moonlakeai.com](https://moonlakeai.com/)
2. [linkedin.com/company/moonlake-ai](https://www.linkedin.com/company/moonlake-ai)
3. [moonlakeai.com/blog/introducing-moonlake-ai](https://moonlakeai.com/blog/introducing-moonlake-ai)
4. [moonlakeai.com/about](https://moonlakeai.com/about)
5. [jobs.ashbyhq.com/Moonlake](https://jobs.ashbyhq.com/Moonlake)

## Other roles at Moonlake

- [Head of Design](https://feeny.ai/job/head-of-design-moonlake-san-francisco-zcejez0vwys1) — San Francisco, CA
- [Head of People Operations](https://feeny.ai/job/head-of-people-operations-moonlake-san-francisco-yj897grtctr3) — San Francisco, CA
- [Member of Technical Staff - Robotics & Simulation](https://feeny.ai/job/member-of-technical-staff-robotics-simulation-moonlake-san-francisco-cwvwzypd4v8s) — San Francisco, CA
- [Member of Technical Staff -  Simulation Engineer](https://feeny.ai/job/member-of-technical-staff-simulation-engineer-moonlake-san-francisco-7qvzm3326680) — San Francisco, CA
- [Member of Technical Staff - Product Engineer](https://feeny.ai/job/member-of-technical-staff-product-engineer-moonlake-san-francisco-rk31eg6t9c6k) — San Francisco, CA