Senior Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles

NVIDIA Gruppe; Santa Clara (CA); On-site; USD 184,000 - 356,500; Full time

Job summary

NVIDIA Gruppe in Santa Clara is seeking a qualified candidate for the role focused on 3D obstacle perception to enhance autonomous driving functionalities. You will design and implement perception models, collaborate across disciplines, and develop efficient deep learning solutions aimed at real-world applications.

Candidates should possess a PhD or equivalent, along with experience in deep learning frameworks like PyTorch. The position offers competitive salaries ranging from $184,000 to $287,500 based on level and experience.

Qualifications

• PhD with 4+ years, MS with 6+ years, or BS with 8+ years of relevant experience.
• Experience in developing deep learning-based perception systems.
• Strong programming skills in Python and/or C++.
• Hands-on experience with data strategy and iterative model improvement.

Responsibilities

• Develop the technical design for 3D obstacle perception.
• Design advanced 3D perception models using multi-sensor fusion.
• Build deep learning models and maintain KPI frameworks.
• Collaborate with various teams for deployment and safety.

Skills

Deep learning-based perception

PyTorch

Python

C++

Data-driven development

Collaboration skills

Education

PhD in Computer Science or related field

MS in Computer Science or related field

BS in Computer Science or related field

Tools

CUDA

Job description

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.

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 Level4, and 224,000 USD – 356,500 USD for Level5. You will also be eligible for equity and benefits.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.