Senior Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles

NVIDIA; United States; On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Senior Perception Engineer to advance its autonomous driving perception stack. You will lead the 3D obstacle perception pipeline, combining multi-camera and multi-sensor fusion to deliver robust object detection and tracking in real time.

You will craft production-grade DL models, optimize for latency on GPUs, and collaborate across data, safety, and software teams to ensure scalable deployment. Strong experience with PyTorch and CUDA is essential.

Qualifications

• PhD/MS/BS with extensive experience in computer science or related field.
• Hands-on experience with deep learning perception systems and production-quality software.
• Strong Python and/or C++ programming skills.
• Experience with PyTorch and GPU-accelerated training/inference.

Responsibilities

• Design and implement 3D obstacle perception models using multi-camera or multi-sensor fusion.
• Develop production-grade perception pipelines with state-of-the-art CNNs and transformers.
• Define KPI frameworks and analyze large datasets to improve accuracy and efficiency.
• Collaborate with safety, systems, and software teams to meet product requirements.
• Contribute to data strategy, labeling, and model-assisted workflows.
• Push for BEV and transformer-based 3D perception in real-time systems.

Skills

Python

C++

PyTorch

Communication

Education

PhD

MS

BS

Tools

CUDA

Job description

Intelligent machines powered by artificial intelligence-computers that can learn, reason, and interact with people-are transforming every industry. GPU-accelerated deep learning provides the foundation for machines to perceive, reason, and solve complex problems. NVIDIA GPUs run deep learning algorithms that simulate aspects of human intelligence, acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.

We are seeking an exceptional Senior Perception Engineer to help design and productize NVIDIA's next-generation autonomous driving perception stack. You will work on the core 3D obstacle perception pipeline, contribute to architecture and algorithm design, and remain deeply hands-on with implementation, including modern transformer-based, multi-modal, and vision-language techniques where they add real value.

What you'll be doing:

• Develop and improve the technical design, architecture, and roadmap for 3D obstacle perception to support end-to-end autonomous driving functionalities, leveraging state-of-the-art CNN and transformer-based architectures where appropriate.
• Design and implement advanced 3D perception models using multi-camera inputs and/or multi-sensor fusion (camera, radar, lidar) for obstacle detection and tracking, including opportunities to explore BEV and transformer-based 3D perception.
• Build efficient, production-grade deep learning models: define objectives with the team, select and prototype architectures, run experiments, and follow best practices for training and evaluation, using techniques such as large-scale pretraining, distillation, and parameter-efficient fine-tuning (e.g., LoRA).
• Help define and maintain KPI frameworks to quantify perception performance; analyze large-scale real and synthetic datasets to identify failure modes and systematically improve accuracy, robustness, and efficiency, incorporating approaches like self-supervised and representation learning when beneficial.
• Contribute to the data strategy for perception: specify data and labeling requirements, help prioritize data collection and annotation, and collaborate with data and ground-truth teams, including model-assisted workflows (e.g., active learning, auto-labeling, vision-language models (VLMs)) and model-in-the-loop tooling.
• Collaborate 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.

What we need to see:

• PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
• Hands-on experience developing deep learning-based perception or closely related systems for complex real-world problems, with strong proficiency in frameworks such as PyTorch and a track record of taking models from prototype to production.
• Proven experience in data-driven development, including close 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 work effectively across multidisciplinary teams.

Ways to stand out from the crowd:

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

#AutonomousVehicles

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits .

Applications for this job will be accepted at least until September 2, 2026.

This posting is for an existing vacancy.

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