AI Engineer, Computer Vision

Niantic Spatial, Inc.

. Implement, train, and evaluate visual localization models in PyTorch .

Posted 10/8/2026full-timeSan Francisco • California • United StatesMid-LevelSenior💰 $165,600 - $221,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in training deep learning models for computer vision tasks using PyTorch, with a strong foundation in visual localization, 3D geometry, and GPU-based training. Proficient in managing large image and 3D datasets while contributing to the full pipeline from data ingestion to model deployment.

Highest-signal resume keywords

Deep Learning Model TrainingVisual Localization3D Geometry UnderstandingGPU-Based TrainingPython Programming

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Deep LearningComputer VisionPyTorchImage RetrievalPose EstimationSLAMStructure-From-Motion3D Dataset ManagementModel DeploymentTraining Loop Optimization

Tools & Technologies

GPU EnvironmentsHigh-Throughput Ingestion PipelinesLocalization Evaluation Benchmarks

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Computer VisionMaster's Degree in Robotics

Industry Keywords

Visual LocalizationPose AccuracyRecallProduction LatencyTraining Data Benchmarking

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Implement, train, and evaluate visual localization models in PyTorch
Iterate on architectures, loss functions, and training loops to improve accuracy on production captures
Contribute to high-throughput ingestion and preprocessing pipelines for imagery, poses, and 3D point clouds
Run training jobs across GPU environments on a 30-billion-image corpus
Help build and maintain localization evaluation benchmarks for pose accuracy, recall, and production latency
Support model deployment through export, inference optimization, and monitoring
Work with Research and the Real-World Test Lab to translate field failures into training data and benchmark improvements
Contribute across the full pipeline from data and training through production service

Requirements

What you’ll need

Experience training deep learning models for computer vision tasks in PyTorch through coursework, research, internships, or early industry work
Foundational understanding of at least one of: 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 parameterizations
Comfort working with large image or 3D datasets, including preprocessing and curation
Familiarity with GPU-based training and ability to reason about 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 in the San Francisco office at least 3 days per week

Benefits

Comp & perks

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