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World Labs

Generates interactive 3D scenes from images

Research Engineer / Scientist - Simultaneous Localization and Mapping

Robotics & Autonomous SystemsConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • At least 6 years of experience working on simultaneous localization and mapping (SLAM), state estimation, robotics perception, or related areas.
  • A strong foundation in probabilistic estimation, optimization, and geometric vision, including bundle adjustment, factor graphs, or Kalman filtering.
  • Deep experience with one or more SLAM paradigms: visual, visual-inertial, lidar, multi-sensor, or hybrid systems.
  • Proficiency in Python and/or C++, with hands-on experience building research or production-grade SLAM systems.
  • Experience with numerical optimization libraries and/or robotics frameworks.
  • Familiarity with learning-based perception or representation learning and how it can augment classical SLAM pipelines.
  • A strong understanding of real-world sensor characteristics, calibration, synchronization, and noise modeling.
  • Ability to work in ambiguous, fast-moving environments and drive projects from concept through deployment.
  • A strong sense of ownership and engineering rigor, with a focus on correctness, stability, and measurable improvements.

Responsibilities

  • Design and implement modern SLAM systems for real-world environments, including visual, visual-inertial, lidar, or multi-sensor configurations.
  • Develop robust localization and mapping pipelines, including pose estimation, map management, loop closure, and global optimization.
  • Research and prototype learning-based or hybrid SLAM approaches that combine classical geometry with modern machine learning methods.
  • Build and maintain scalable state estimation frameworks, including factor graph optimization, filtering, and smoothing techniques.
  • Develop sensor fusion strategies that integrate cameras, IMUs, depth sensors, lidar, or other modalities to improve robustness and accuracy.
  • Analyze failure modes in real-world SLAM deployments, such as perceptual aliasing, dynamic scenes, and drift, and design principled solutions.
  • Create evaluation frameworks, benchmarks, and metrics to measure SLAM accuracy, robustness, and performance across large datasets.
  • Optimize performance across the stack, including real-time constraints, memory usage, and compute efficiency, for large-scale and production systems.
  • Collaborate with reconstruction, simulation, and infrastructure teams to integrate SLAM outputs with downstream world modeling and rendering pipelines.
  • Contribute to technical direction by proposing research ideas, mentoring teammates, and helping define best practices for localization and mapping across the organization.

About the Company

World Labs

Generates interactive 3D scenes from images

World Labs is building tools for spatial intelligence through Large World Models (LWMs) that can perceive, generate, and interact with 3D environments. Its main product is an AI system that can turn a single image into an entire interactive 3D scene, useful for gaming, simulation, and digital content creation. The technology works by taking a 2D image and generating full 3D representations and interactions, forming a platform or service for developers to create 3D content and experiences. Unlike many competitors, World Labs focuses specifically on zero-shot 3D scene generation from a single image and providing end-to-end 3D content creation capabilities as a scalable platform. Its goal is to enable rapid creation and manipulation of rich 3D worlds for developers and companies in gaming, simulation, and digital media.

Company size
51-200
Company stage
Acquired
Total funding
$1.2B
Headquarters
San Francisco, CA
Founded
2024

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