Research Engineer, World Models

Job Description

Job Description

The Mission

At GRAM, we believe the next great leap for humanity will be physical, not digital. What AGI is to bits, Self-Replication (SR) is to atoms. As an SR research and deployment company, our mission is to make humanity galactic by enabling physical exponential growth. To achieve this, we are conducting foundational research across general-purpose robotics, artificial intelligence, biology, and materials science to enable SR within our lifetimes.

Our first step is to challenge the consensus that robots should look like us. We believe true progress comes from optimizing for function over form. We are creating a new embodiment for intelligence, designed from first principles to build the future physical economy, on and off-world.

The Role

A machine's body is only as capable as the mind that drives it. This role is for the engineers who breathe life into the hardware, teaching our Insectoid robot how to move, perceive, and act in the physical world. You will be responsible for creating the algorithms and software that form the robot's intelligence, from low-level motor skills to high-level reasoning.

This is an opportunity to solve foundational problems in AI and robotics on a novel morphology that has no precedent. You will work at the frontier of control theory, reinforcement learning, and computer vision to give our robot the ability to navigate and interact with complex, unstructured environments, creating the intelligent foundation for its ultimate mission.

Key Responsibilities :

Design and train large-scale, self-supervised models that learn the dynamics of the physical world from raw sensor data.

Develop predictive models that can "imagine" future outcomes of potential actions, to be used for planning and improving sample efficiency in RL.

Build generative models that can reconstruct and understand complex 3D scenes from multi-modal sensor inputs.

Integrate learned world models into the robot's planning and control stacks to enable more intelligent and proactive behavior.

Stay at the absolute frontier of academic research in representation learning and generative modeling, applying new breakthroughs to our platform.

About You

You are a first-principles thinker who is energized by solving problems that have no playbook. You are drawn to ambitious, long-term missions and want to build technology that fundamentally changes our physical capabilities. You thrive in a high-agency environment where you are given the ownership and resources to tackle core challenges.

Basic Qualifications :

MS in Computer Science or a related field with 3+ years of experience in machine learning.

Expert proficiency with Python and deep learning frameworks (e.g., PyTorch, TensorFlow).

A strong foundation in modern deep learning architectures, including Transformers, VAEs, and GANs.

Experience training large-scale models on large datasets.

Preferred Qualifications :

A PhD with a focus on deep learning, generative models, or representation learning.

A track record of publications in top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR).

Experience applying world models or predictive models in a robotics or control context.

Expertise in self-supervised and unsupervised learning techniques.

Location

This is an on-site role at our research lab in El Segundo, California. We offer significant relocation assistance for exceptional candidates.

Interview Process

After submitting your application, we review your portfolio and any exceptional work you've shipped. If your application demonstrates the caliber we seek, you'll enter our interview process, which is designed for speed and substance. We aim to complete it within one week from start to finish.

Compensation

Your total compensation reflects both the significance of early-stage equity and competitive market rates. The following is the general framework for all roles at GRAM.

• Company-Wide Base Salary Range : $75,000 - $300,000 USD, calibrated to your impact potential
• Equity : Substantial ownership stake befitting founding team members
• Benefits : Health, dental, and vision coverage; all meals are paid for; relocation assistance

GRAM is an equal opportunity employer. We evaluate solely on capability and drive.

Why Join?

We are an early, focused team of scientists and engineers building the system that builds itself. GRAM is funded by leading investors and long-term visionaries. We operate without bureaucracy. Ownership and leadership flow to those who demonstrate exceptional capability, and every team member works directly on our core technology. We are based in El Segundo, the heart of America's industrial future, focused on solving one of the most important problems of our time.