Deep Learning Engineer Intern – 3D Reconstruction

Computer Vision Engineer Intern | PlusAIThe Tone:

This is an internship at PlusAI, headquartered in Silicon Valley with operations in the United States and Europe. PlusAI is a Physical AI company that builds AI-based virtual driver software for factory‑built autonomous trucks. This role is crucial for developing the foundational 3D/4D digital twin technology that enables rigorous simulation and testing of autonomous driving systems, directly impacting the deployment of next‑generation trucks.

By contributing to advanced scene reconstruction, this intern will help accelerate the validation and verification processes essential for bringing autonomous trucking to reality.

• Role:
  Internship
• Location:
  
  In-person, Silicon Valley, US
• Pay: $19–$65 hourly
• Team:
  Supports the Simulation and Perception teams
• Mission:
  Generate realistic 3D/4D scene reconstructions and sensor data to simulate driving environments for autonomous truck development and testing.
• Tech Stack:
  PyTorch, Tensorflow, Jax, 3D Gaussian Splatting (3
  
  DGS), NeRFs, camera, LiDAR, IMU, GPS

• Construct Digital Twins:
  Develop and optimize pipelines to reconstruct high‑fidelity, multi‑modal 3D representations of key driving routes using recorded vehicle data including camera, LiDAR, IMU, and GPS.
• Implement Next‑Gen Tech:
  Apply state‑of‑the‑art neural rendering and view‑synthesis techniques, such as 3D Gaussian Splatting (3
  
  DGS) and NeRFs, to handle challenging real‑world lighting, weather, and dynamic objects.
• Drive Validation & Verification (V&V):
  Integrate reconstructed environments into our perception testing framework to stress‑test object detection, tracking, and edge‑case scenarios.
• Evaluate Multi‑Modal Accuracy:
  Ensure alignment and geometric consistency between different sensor modalities within the reconstructed digital twin.
• Collaborate & Scale:
  Work closely with the Simulation and Perception teams to turn research prototypes into robust, scalable tooling that directly impacts our production deployment timeline.

• Background:
  Student pursuing a Master’s or PhD degree in Computer Science, Electrical Engineering, mathematics, statistics, or a related technical field.
• Experience:
  
  Prior experience implementing deep learning models in at least one deep learning framework.
• Skills:
  
  Deep understanding of machine learning principles and methodologies, experience with deep learning frameworks (PyTorch, Tensorflow, Jax).
• Bonus:
  Past experiences in deep learning projects involving object detection, motion tracking or semantic segmentation, experience with 3D Vision, or a publication record in relevant venues (CVPR, ICLR, ICCV, ECCV, NeurIPS, AAAI, SIGGRAPH).