Sr. Software Engineer - 3D Scene Reconstruction

This is a remote position.

Sr. Software Engineer - 3D Scene Reconstruction  - Remote Job, 3-5+ Year Experience

Annual Income: $100K - $122K

About us: Patterned Learning is a platform that aims to help developers code faster and more efficiently. It offers features such as collaborative coding, real-time multiplayer editing, and the ability to build, test, and deploy directly from the browser. The platform also provides tightly integrated code generation, editing, and output capabilities.

About the job

In this role, you will collaborate with ML researchers, technical artists, and simulation engineers to build realistic, accurate and detailed 3D models using machine learning from a variety of data sources. This role demands a blend of technical proficiency and a keen eye for detail to ensure the reconstructed scenes are as lifelike and accurate as possible.

Responsibilities

• Solid understanding of the state of the art, practical scene reconstruction techniques including but not limited to neural, volumetric and point-cloud methods.
  

• Must have experience in evaluating reconstruction output, ensuring the generated scenes meet quality and accuracy requirements.
  

• Write high-quality, performant, and maintainable codeImprove rendering and tooling for generating photoreal data at scale.
  
  

Qualifications

• Experience in 3D rendering for simulation, games, or VFX
  

• Experience with NeRF, SDF, or an equivalent technique
  

• High proficiency in C++ and Python
  

• Experience building ML models
  
  

Bonus Qualifications

• Experience in computer vision or roboticsExperience with lidar, radar, or camera simulation
  

• Experience with 3D generative ML
  

• Experience automating 3D content pipelines using apps like Houdini, Maya, or Blender
  

• Experience in distributed systems and cloud computing platforms
  

Why Patterned Learning LLC?

Patterned Learning can provide intelligent suggestions, automate repetitive tasks, and assist developers in writing code more effectively. This can help reduce coding errors, improve productivity, and accelerate the development process.

The pattern recognition is particularly relevant in the context of coding. Neural networks, especially deep learning models, are commonly employed for pattern detection and classification tasks. These models simulate human decision-making and can identify patterns in data, making them well-suited for tasks like code analysis and generation.