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Niantic Spatial, Inc.
Niantic Spatial, Inc.
201 – 500 Employees
ConsultingDefenseLogistics
Niantic Spatial, Inc. develops geospatial AI for building machine-readable representations of the physical world. Its platform combines ground-based and aerial sensor data to produce high-fidelity, geo-referenced 3D digital twins, support visual localization where GPS is unreliable, and add semantic meaning to mapped environments. Through products for capturing, reconstructing, localizing, and understanding space, the company serves robotics, public sector and defense, industrial, and large-venue use cases with SDKs and enterprise services for developers and organizations.
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Computer Vision AI Engineer

Train computer vision localization models for Niantic Spatial’s physical AI and geospatial platform. Build data pipelines, evaluation benchmarks, and production inference systems.

USUnited StatesCACalifornia
$165,600 – $221,000 / year
HybridFull-timeMiddleSeniorEnglish RequiredComputer Vision EngineerMachine Learning Engineer
PythonPyTorch

Description

  • Develop, train, and assess visual localization models using PyTorch.
  • Refine model architectures, loss functions, and training loops to improve accuracy on production imagery.
  • Help build high-throughput pipelines to ingest and preprocess images, pose data, and 3D point clouds.
  • Run model training on GPU systems using a corpus of 30 billion images.
  • Build and maintain benchmarks that measure localization pose accuracy, recall, and production latency.
  • Prepare models for deployment through export, inference optimization, and monitoring.
  • Partner with Research and the Real-World Test Lab to turn field failures into training data and benchmark improvements.
  • Contribute throughout the pipeline, from data preparation and training to production services.

Requirements

  • Experience training PyTorch deep learning models for computer vision through coursework, research, internships, or early industry roles.
  • Foundational knowledge of at least one area: visual localization, learned feature matching, image retrieval, pose estimation, SLAM, or structure-from-motion.
  • Understanding of 3D geometry, including camera models, epipolar geometry, and pose representations.
  • Comfort working with large image or 3D datasets, including their preprocessing and curation.
  • Familiarity with GPU-based training and the ability to assess training runs.
  • Strong Python skills.
  • Bachelor’s or master’s degree in computer science, computer vision, robotics, or a related field, or equivalent practical experience.
  • Ability to work from the San Francisco office at least three days per week.

Benefits

  • Annual bonus
  • Equity
  • Medical coverage
  • Dental coverage
  • Vision coverage
  • 401(k)
  • Comprehensive benefits package

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