Luma

1 month ago

Simulation Researcher/Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Design and build high-fidelity robotics simulation environments and evaluation pipelines, blending generative 3D content with physics-based systems. Collaborate across world-model and policy-learning researchers to enable scalable, trainable simulations and practical sim-to-real transfer for robot policies.

Location: Los Angeles

Workplace: Hybrid

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Design simulation environments that are visually rich, physically plausible, and trainable at scale — a hybrid of generative rollouts and physics-engine-based scenes.
•Build the evaluation harness that tells us whether our world model is good enough to train robots on (sim-to-real gap, physical consistency, long-horizon coherence).
•Develop differentiable and GPU-accelerated simulation pipelines where they unlock new training signal.
•Drive the asset, scene, and task generation pipelines — including using Luma's own generative stack to bootstrap diversity.
•Collaborate with world-model researchers (upstream) and policy-learning researchers (downstream).

Pay and Benefits

Salary: USD 250,000 - 450,000 annually

Key Requirements

•Strong background in robotics simulation, computer graphics, physics-based modeling, or generative 3D — degree or equivalent practical record.
•Fluency in Python and C++; deep familiarity with at least one production physics engine (Isaac Sim/Lab, MuJoCo, Bullet, PhysX, Drake).
•Track record of building simulation systems other people actually used.

Experience:RoboticsSimulationGraphicsGenerative 3D

Education:Bachelor's

Skills:CommunicationProblem-solving

Tech Stack:PythonC++Isaac SimMuJoCoBulletPhysXDrakeGPUGPU-accelerated

Company Brief

Luma

Develops AI-powered tools for capturing, editing, and rendering high-quality 3D scenes from photos and videos, enabling creators to generate photorealistic 3D assets and spatial experiences.

Industry: AR/VR & Spatial Computing

Website

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Luma

1 month ago

Simulation Researcher/Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: Los Angeles

Workplace: Hybrid

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Design simulation environments that are visually rich, physically plausible, and trainable at scale — a hybrid of generative rollouts and physics-engine-based scenes.
•Build the evaluation harness that tells us whether our world model is good enough to train robots on (sim-to-real gap, physical consistency, long-horizon coherence).
•Develop differentiable and GPU-accelerated simulation pipelines where they unlock new training signal.
•Drive the asset, scene, and task generation pipelines — including using Luma's own generative stack to bootstrap diversity.
•Collaborate with world-model researchers (upstream) and policy-learning researchers (downstream).

Pay and Benefits

Salary: USD 250,000 - 450,000 annually

Key Requirements

•Strong background in robotics simulation, computer graphics, physics-based modeling, or generative 3D — degree or equivalent practical record.
•Fluency in Python and C++; deep familiarity with at least one production physics engine (Isaac Sim/Lab, MuJoCo, Bullet, PhysX, Drake).
•Track record of building simulation systems other people actually used.

Experience:RoboticsSimulationGraphicsGenerative 3D

Education:Bachelor's

Skills:CommunicationProblem-solving

Tech Stack:PythonC++Isaac SimMuJoCoBulletPhysXDrakeGPUGPU-accelerated

Company Brief

Luma

Develops AI-powered tools for capturing, editing, and rendering high-quality 3D scenes from photos and videos, enabling creators to generate photorealistic 3D assets and spatial experiences.

Industry: AR/VR & Spatial Computing

Website