AI Research Scientist

Role Summary

Why RoboForce

RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.

We are looking for a Senior / Staff AI Research Scientist, Foundation Models to advance robotic embodied intelligence. In this role, you will develop algorithms that enable robots to understand their environment, interpret and execute tasks, and communicate seamlessly with humans — with a particular focus on building and training world models that allow robots to predict, plan, and generalize across complex physical tasks.

Responsibilities

• Design and deploy vision-language(-action) models (VLM/VLA) for contextual understanding and generalized robot action policies.
• Develop and train world models for action-conditioned prediction, long-horizon planning, and environment simulation — enabling robots to reason about the consequences of their actions before execution.
• Research approaches to improve world model fidelity using multi-modal inputs including vision, language, proprioception, and spatial representations.
• Develop foundation models with spatial reasoning capabilities to achieve high-precision robotic actions.
• Integrate multi-modal data sources (vision, language, speech, etc.) to enable natural human-robot communication.
• Optimize and deploy models as production-grade solutions on RoboForce robotic platforms.

Requirements

• PhD degree in Machine Learning, Robotics, or related field, or Master's degree with 4+ years of relevant experience.
• Proficiency in Python and deep learning frameworks (e.g., PyTorch, JAX).
• Expertise in large foundation models (VLM, VLA, etc.).
• Strong understanding of world model architectures and action-conditioned generative modeling for robot learning.
• Decent understanding of multimodal models, modern ML architectures (transformers, diffusion models, etc.).
• Requires 5 days/week in-office collaboration with the teams.

Bonus Qualifications

• Experience with video generation or prediction models (e.g., diffusion-based video models, autoregressive video transformers) and their application to world modeling or synthetic data generation for robot learning.
• Strong publication record at top conferences (NeurIPS, ICML, CVPR, ICCV, CoRL, ICRA, or equivalent).
• Expertise in neural network deployment (e.g., TensorRT) and GPU programming with CUDA.
• Proven ability to design scalable experimentation and data pipelines.

Benefits

• Competitive stock options/equity programs.
• Health, dental, and vision insurance, 401(k) plan.
• Visa sponsorship and green card support for qualified candidates.
• Lunches and dinners, a fully stocked kitchen, and regular team-building events.

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