5+ years of experience in ML or computer vision systems
Bachelor's degree in computer science, physics, robotics, or equivalent
Hands-on experience with 3D reconstruction techniques like 3D Gaussian Splatting and NeRFs
Strong foundation in multi-view geometry and differentiable rendering
Proficiency in Python, PyTorch, and C++/CUDA
Ability to convert research into production-quality software
Strong problem-solving skills and comfort with ambiguity
Responsibilities
Advance learning-based reconstruction methods to improve product fidelity and scalability
Push neural reconstruction limits for dynamic driving scenes
Explore feed-forward reconstruction approaches for cost reduction
Define evaluation metrics and validation workflows for reconstruction fidelity
Collaborate with customers to implement technical solutions
Work with cross-functional teams to deliver end-to-end solutions
Take ownership of technical components and influence product decisions
Benefits
Collaborative work environment with cross-functional teams
Opportunity to work on cutting-edge technology in autonomous vehicles
Direct impact on the development of data-driven simulation products
Engagement with leading OEMs in the automotive industry
Encouragement to apply even if not meeting every requirement
Full Job Description
About the role and team
We are looking for senior machine learning engineers to advance the core reconstruction technology behind Neural Simulation, our state-of-the-art product for turning real-world driving data into high-fidelity, photorealistic simulation environments. As part of this team, you will push the boundaries of what the product can do, raising reconstruction quality, scaling to ever-larger volumes of data, and making it more useful for customers who rely on it to train and validate their autonomy systems. Your work will directly shape how the largest OEMs in the world develop the next generation of data-driven autonomous vehicles.
This role is ideal for engineers who thrive at the intersection of 3D computer vision, graphics, and machine learning, and who are excited to take a state-of-the-art product further by bringing the latest research into production and solving the hardest simulation gaps in Physical AI.
At Applied Intuition, you will:
Advance the learning-based reconstruction methods at the core of our product, such as 3D Gaussian Splatting and NeRFs, bringing the latest research into production to improve fidelity, robustness, and scalability
Push the limits of neural reconstruction for large-scale, dynamic driving scenes, including:
Dynamic actor reconstruction and scene editing
Novel view synthesis and multi-sensor rendering (camera, LiDAR)
Scaling reconstruction quality and throughput across large volumes of fleet data
Explore and productionize feed-forward reconstruction approaches that reduce per-scene optimization cost and enable reconstruction at scale
Define and build evaluation metrics, benchmarks, and validation workflows that measure reconstruction fidelity and sim-to-real gap
Work closely with customers to understand their pain points and implement technical solutions in the Neural Simulation product
Collaborate closely with Infra, Autonomy, Research and other product teams to deliver end-to-end solutions
Take ownership of critical technical components and influence architecture and product decisions
We're looking for someone who has:
5+ years of experience developing and shipping ML or computer vision systems
A 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
Don't meet every single requirement? If you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
About Applied Intuition
Applied Intuition is a software company that provides a simulation platform for autonomous vehicles. The platform allows developers to test and validate their autonomous vehicle software in a virtual environment before deploying it on real vehicles. Applied Intuition was founded in 2017 and is headquartered in Mountain View, California.
