Senior Machine Learning Engineer - 3D Reconstruction
$190k - $260k • Sunnyvale • FullTime
Posted 11d ago
Job Location
Sunnyvale
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Machine Learning Engineer
About the job
Applied Intuition is seeking a Senior Machine Learning Engineer to advance the core reconstruction technology behind their Neural Simulation product. This role involves transforming real-world driving data into high-fidelity simulation environments, pushing the boundaries of reconstruction quality, scaling data processing, and enhancing product utility for customers training autonomy systems. The engineer will directly influence the development of next-generation autonomous vehicles for major OEMs, working at the intersection of 3D computer vision, graphics, and machine learning to bring cutting-edge research into production and solve complex simulation challenges in Physical AI.
Responsibilities
- Advance learning-based reconstruction methods like 3D Gaussian Splatting and NeRFs, bringing 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, scene editing, 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 to reduce per-scene optimization costs and enable reconstruction at scale.
- Define and build evaluation metrics, benchmarks, and validation workflows to measure reconstruction fidelity and sim-to-real gap.
- Work closely with customers to understand pain points and implement technical solutions.
- Collaborate 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.
Requirements
- 5+ years of experience developing and shipping ML or computer vision systems.
- Bachelor's degree in computer science, physics, robotics, or equivalent.
- Strong hands-on experience with modern learning-based 3D reconstruction techniques (e.g., 3D Gaussian Splatting, NeRFs).
- Solid foundation in multi-view geometry, camera models, and differentiable rendering.
- Proficiency in Python and PyTorch.
- Proficiency in C++ and/or CUDA.
- Proven ability to turn research ideas into robust, production-quality software.
- Strong problem-solving skills and comfort with ambiguity.