Senior Machine Learning Engineer - 3D Reconstruction

• 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

• 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

• 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. Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.