Senior Deep Learning Engineer, 4D Foundation Model

NVIDIA
Shanghai
Full timeFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: bachelorsSkills: ["Debugging","Metrics","Controlled experiments","Collaboration","Communication"]

Develop and train deep learning models for 4D world modeling that reconstruct and interpret dynamic environments from multi-camera video and sensor data. Build architectures for neural rendering, 3D/4D reconstruction, object-centric representations, and mapping, and explore diffusion, flow-based, and video-generation methods. Scale distributed training pipelines, create visualization tools for model debugging, and integrate trained models into simulation workflows for autonomous vehicles and Physical AI applications.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
NVIDIA
NVIDIA
1 day ago

Senior Deep Learning Engineer, 4D Foundation Model

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live

Job Summary

Develop and train deep learning models for 4D world modeling that reconstruct and interpret dynamic environments from multi-camera video and sensor data. Build architectures for neural rendering, 3D/4D reconstruction, object-centric representations, and mapping, and explore diffusion, flow-based, and video-generation methods. Scale distributed training pipelines, create visualization tools for model debugging, and integrate trained models into simulation workflows for autonomous vehicles and Physical AI applications.
Location: Shanghai
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Develop, train, and evaluate models for accurate, temporally consistent reconstruction of dynamic scenes.
  • •Design architectures for Gaussian prediction, neural rendering, 3D/4D reconstruction, object-centric representations, and mapping.
  • •Model geometry, appearance, semantics, motion, and interactions to enable realistic, controllable simulation environments.
  • •Explore diffusion, flow-based, and video-generation approaches for novel views, scene completion, temporal prediction, and world generation.
  • •Scale data handling and distributed training pipelines for multi-camera video, vehicle poses, perception signals, and other sensor data.

Key Requirements

  • •5+ years of relevant experience and a BS, MS, or PhD in a related technical field (or equivalent practical experience).
  • •Proficiency in Python and experience developing and training models with PyTorch or a comparable framework.
  • •Foundational knowledge in deep learning and computer vision areas such as 3D/multi-view geometry, neural rendering, or generative modeling.
  • •Experience training and evaluating models using large image/video/3D/multimodal datasets.
  • •Ability to work with camera models, calibration, coordinate systems/geometry, motion, uncertainty, and temporal consistency.
Experience:5+ yearsComputer visionMulti-view geometryNeural renderingGenerative modelingMultimodal datasetsAutonomous drivingRoboticsPhysical AI
Education:Bachelor's
Skills:DebuggingMetricsControlled experimentsCollaborationCommunication
Tech Stack:PythonPyTorchCUDAGPUsDistributed trainingGaussian splattingNeRFsNeural renderingDiffusion modelsFlow matchingVideo generation3D reconstructionMultimodal modelingCamera models

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
WebsiteLinkedInGlassdoor