Lead the development of efficient, production-grade deep learning models: define objectives, select architectures, guide experimentation, and establish best practices for training and evaluation, using techniques such as large-scale pretraining, distillation, and parameter-efficient fine-tuning (e.g., LoRA).
Define and drive 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 modern approaches like self-supervised and representation learning when beneficial.
Lead data strategy for perception: specify data and labeling requirements, prioritize data collection and annotation, and collaborate closely with data and ground-truth teams to maximize impact, including model-assisted workflows (e.g., active learning, auto-labeling, VLMs) and advanced model-in-the-loop tooling.
Partner with safety, systems, and software teams to ensure perception solutions meet stringent product requirements for safety, latency, resource usage, and software robustness, and are ready for deployment at scale.
Provide technical leadership and mentorship to other engineers, influencing design and implementation across the broader perception and autonomy teams.
What we need to see
15+ years of 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.
Demonstrated technical leadership as a senior or principal-level individual contributor: owning features or subsystems end-to-end, setting technical direction, making architectural decisions, and coordinating across teams.
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 a history of 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/PhD in Computer Science, Electrical Engineering, or related fields (or equivalent experience).
Ways to stand out from the crowd
Proven track record leading the design and deployment of 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 other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.
