Machine Learning Engineer, Sr.

About Applied Intuition

Applied Intuition, Inc. is a Silicon Valley company developing digital infrastructure for physical AI. Founded in 2017, the company provides tools, infrastructure, operating systems, and autonomous technology for industries including automotive, defense, trucking, construction, mining, and agriculture.

Eighteen of the world's top 20 automakers, along with the United States military and its allies, use Applied Intuition's solutions. The company is headquartered in Sunnyvale, California, with offices across the United States and internationally, including Bangalore, London, Munich, Seoul, and Tokyo.

About the Role

Applied Intuition is seeking Senior Machine Learning Engineers to advance the reconstruction technology behind its Neural Simulation product. The team transforms real-world driving data into high-fidelity, photorealistic simulation environments that help customers train and validate autonomous driving systems.

This role focuses on the intersection of 3D computer vision, computer graphics, and machine learning. You will develop and scale neural reconstruction methods, bring emerging research into production, and address technical challenges involving dynamic driving scenes, multi-sensor rendering, and simulation fidelity. Your work will contribute to the tools used by major automotive manufacturers to develop next-generation autonomous vehicles.

Key Responsibilities

• Advance learning-based 3D reconstruction methods, including 3D Gaussian Splatting and Neural Radiance Fields (NeRFs), to improve fidelity, robustness, and scalability.

• Develop neural reconstruction capabilities for large-scale, dynamic driving scenes.

• Work on dynamic actor reconstruction, scene editing, novel view synthesis, and multi-sensor rendering for cameras and LiDAR.

• Improve reconstruction quality and processing throughput across large volumes of fleet driving data.

• Explore and productionize feed-forward reconstruction approaches that reduce per-scene optimization costs and support reconstruction at scale.

• Define and develop evaluation metrics, benchmarks, and validation workflows to measure reconstruction fidelity and the sim-to-real gap.

• Work directly with customers to understand their challenges and implement technical solutions within the Neural Simulation product.

• Collaborate with infrastructure, autonomy, research, and product teams to deliver end-to-end solutions.

• Own critical technical components and contribute to architecture and product decisions.

• Translate the latest machine learning and computer vision research into reliable, production-quality software.

Required Qualifications

• At least five years of experience developing and deploying machine learning or computer vision systems.

• Bachelor's degree in Computer Science, Physics, Robotics, or an equivalent qualification.

• Strong hands-on experience with modern learning-based 3D reconstruction techniques, such as 3D Gaussian Splatting and NeRFs.

• Solid understanding of multi-view geometry, camera models, and differentiable rendering.

• Proficiency in Python and PyTorch, along with C++ and/or CUDA.

• Demonstrated ability to turn research ideas into robust, production-quality software.

• Strong problem-solving skills and the ability to work through ambiguous technical challenges.

Preferred Qualifications

• Experience with feed-forward or generalizable Gaussian Splatting and reconstruction models.

• Background in computer vision techniques such as Structure from Motion (SfM), Simultaneous Localization and Mapping (SLAM), or photogrammetry.

• Background in computer graphics, including rendering, rasterization, or ray tracing.

• Experience shipping machine learning products with clearly defined evaluation metrics and benchmarks.

• Experience in autonomous driving or robotics, including work with multi-sensor data such as cameras, LiDAR, and radar.

• Peer-reviewed research published at conferences such as CVPR, ICCV/ECCV, NeurIPS, SIGGRAPH, ICRA, or IROS.

• Master's degree or PhD in Computer Science, Physics, Robotics, or a related field.

Work Arrangement

Applied Intuition operates primarily as an in-office company. Full-time employees are expected to work from their Applied Intuition office five days per week. Occasional flexibility may be available for remote work or schedule adjustments to accommodate personal commitments. This in-office expectation does not apply to contractor positions.

Equal Employment Opportunity

Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. The company complies with applicable federal requirements prohibiting discrimination against qualified individuals based on protected veteran status or disability, as well as discrimination based on race, color, religion, sex, sexual orientation, gender identity, or national origin. It also follows applicable affirmative action requirements and federal labor law employee-notice obligations.

For US-based roles, Applied Intuition provides reasonable accommodations during the application and interview process for disabled veterans and other applicants with disabilities or medical conditions. Requesting an accommodation will not affect an applicant's candidacy, and applicants do not need to disclose the nature of their condition to request one. Accommodation requests can be directed to careers@applied.co.