Senior Machine Learning Engineer - 3D Reconstruction

The role

You will advance learning-based reconstruction methods like 3D Gaussian Splatting and NeRFs to improve Neural Simulation. You will work on dynamic actor reconstruction, novel view synthesis, and scaling reconstruction quality for large volumes of fleet data.

What you will do

• Advance learning-based reconstruction methods such as 3D Gaussian Splatting and NeRFs
• Push limits of neural reconstruction for large-scale, dynamic driving scenes
• Perform dynamic actor reconstruction and scene editing
• Perform novel view synthesis and multi-sensor rendering
• Scale reconstruction quality and throughput across large volumes of fleet data
• Explore and productionize feed-forward reconstruction approaches
• Define and build evaluation metrics, benchmarks, and validation workflows
• Work closely with customers to implement technical solutions
• Collaborate with Infra, Autonomy, Research and other product teams
• Take ownership of critical technical components and influence architecture and product decisions

Required qualifications

• 5+ years of experience developing and shipping ML or computer vision systems
• Minimum of a Bachelor's degree in computer science, physics, robotics, or equivalent
• Strong hands-on experience with modern learning-based 3D reconstruction techniques, such as 3D Gaussian Splatting and NeRFs
• A solid foundation in multi-view geometry, camera models, and differentiable rendering
• Proficiency in Python and PyTorch, along with C++ and/or CUDA
• A proven ability to turn research ideas into robust, production-quality software
• Strong problem-solving skills and comfort with ambiguity

Nice to have

• Experience with feed-forward or generalizable Gaussian Splatting and reconstruction models
• A background in computer vision (e.g., SfM, SLAM, photogrammetry) and/or computer graphics (e.g., rendering, rasterization, ray tracing)
• A track record of shipping ML products with clearly defined evaluation metrics and benchmarks
• Experience in autonomous driving or robotics, including working with multi-sensor data (camera, LiDAR, radar)
• Peer-reviewed research at conferences such as CVPR, ICCV/ECCV, NeurIPS, SIGGRAPH, ICRA, or IROS
• A Master's degree or PhD in computer science, physics, robotics, or related fields

About the company

Applied Intuition, Inc. is a Silicon Valley company creating digital infrastructure for physical AI. It services the automotive, defense, trucking, construction, mining and agriculture industries.