Principal Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles

Details

NVIDIA is seeking an exceptional Principal Perception Engineer to lead the design and productization of its next-generation autonomous driving perception stack. This senior individual contributor role provides broad technical leadership across 3D obstacle perception, including architecture, algorithms, implementation, cross-functional execution, and mentorship. The role involves modern transformer-based, multi-modal, and vision-language techniques where they provide value.

Responsibilities

• Own the technical vision, architecture, and roadmap for 3D obstacle perception supporting end-to-end autonomous driving functionalities, leveraging CNN and transformer-based architectures where appropriate.
• Design and develop advanced 3D perception models using multi-camera inputs and/or multi-sensor fusion, including camera, radar, and lidar, for obstacle detection and tracking.
• Explore BEV and transformer-based 3D perception approaches.
• Lead the development of efficient, production-grade deep learning models by defining objectives, selecting architectures, guiding experimentation, and establishing training and evaluation best practices.
• Apply techniques such as large-scale pretraining, distillation, and parameter-efficient fine-tuning, including LoRA.
• Define and drive KPI frameworks to quantify perception performance.
• Analyze large-scale real and synthetic datasets to identify failure modes and improve accuracy, robustness, and efficiency.
• Apply self-supervised learning and representation learning when beneficial.
• Lead data strategy for perception, including data and labeling requirements, data collection and annotation priorities, and collaboration with data and ground-truth teams.
• Develop model-assisted workflows using active learning, auto-labeling, vision-language models, and advanced model-in-the-loop tooling.
• Partner with safety, systems, and software teams to ensure perception solutions meet product requirements for safety, latency, resource usage, and software robustness, and are ready for deployment at scale.
• Provide technical leadership and mentorship to engineers and influence design and implementation across perception and autonomy teams.

Requirements

• 15+ years of hands-on experience developing deep learning-based perception or closely related systems for complex real-world problems.
• Strong proficiency in frameworks such as PyTorch and a track record of taking models from prototype to production.
• Demonstrated senior or principal-level technical leadership as an individual contributor, including end-to-end ownership of features or subsystems, technical direction, architectural decisions, and cross-team coordination.
• Experience in data-driven development and collaboration with data, labeling, and ground-truth teams on data strategy, labeling quality, and iterative model improvement.
• Strong programming skills in Python and/or C++, with experience building reliable, high-performance, production-quality software.
• Excellent communication and collaboration skills, with the ability to influence, align, and drive consensus across multidisciplinary teams.
• BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.

Preferred Qualifications

• Experience leading the design and deployment of perception solutions for autonomous driving or robotics using camera-based deep learning at scale.
• Experience architecting and deploying DNN-based perception pipelines on embedded or real-time platforms, including optimization for latency, memory, and compute constraints.
• Experience with CNNs, transformers, large-scale pretraining, parameter-efficient fine-tuning such as LoRA, or vision-language models.
• Strong publication record or recognized contributions in deep learning, computer vision, or autonomous systems at conferences or journals such as CVPR, ICCV, NeurIPS, or IROS.
• Deep understanding of 3D computer vision fundamentals, including camera modeling and calibration, intrinsic and extrinsic parameters, multi-view geometry, and 3D representations.
• Experience applying 3D computer vision concepts in transformer-based 3D or BEV perception pipelines.
• Experience with CUDA development and optimization of training or inference pipelines through custom CUDA kernels or other GPU-accelerated components.

Compensation And Benefits

The base salary range is USD 272,000–431,250, determined based on location, experience, and the pay of employees in similar positions. The role also includes eligibility for equity and benefits.

Applications for this job will be accepted at least until July 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.