# Research Engineer / Scientist (SLAM)

**Company:** [World Labs](https://hotfix.jobs/companies/world-labs)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Experience:** 6+ years
**Skills:** Slam, State Estimation, Computer Vision, Python, C++, Factor Graphs, Bundle Adjustment, Kalman Filtering, Sensor Fusion, ROS, Numerical Optimization, Machine Learning, Lidar, Imu, Probabilistic Estimation
**Posted:** 2026-04-22

> Designs, implements, and advances state-of-the-art SLAM systems for robust spatial understanding from sensor data in dynamic environments. Requires 6+ years in SLAM/state estimation, proficiency in Python/C++, and expertise in probabilistic methods and sensor fusion.

## Job Description

## 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 (e.g., perceptual aliasing, dynamic scenes, 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 ensure SLAM outputs integrate cleanly with downstream world modeling and rendering pipelines.
- Contribute to technical direction by proposing new research ideas, mentoring teammates, and helping define best practices for localization and mapping across the organization.

## Requirements

- **6+ years** of experience working on SLAM, state estimation, robotics perception, or related areas.
- Strong foundation in probabilistic estimation, optimization, and geometric vision (e.g., bundle adjustment, factor graphs, 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.
- Strong understanding of real-world sensor characteristics, calibration, synchronization, and noise modeling.
- Proven ability to work in ambiguous, fast-moving environments and drive projects from concept through deployment.
- A strong sense of ownership and engineering rigor: you care deeply about correctness, stability, and measurable improvements.
- Enjoy collaborating with a small, high-caliber team and raising the technical bar through thoughtful design, experimentation, and code quality.

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