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Senior Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles

NVIDIA· Engineer, Sys SW
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Hybrid (Santa Clara, CA), Hybrid (Remote (US)), Remote, Hybrid (WA, Remote)$184k - $287.5kFull-timePosted 3mo ago

About the role

Senior role focused on designing and productizing NVIDIA’s autonomous driving perception stack, with hands-on implementation of 3D obstacle perception using CNN/transformer architectures, multi-sensor fusion, and vision-language techniques for scalable deployment.

Responsibilities

  • 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 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.

Qualifications

  • PhD with 4+ years, MS with 6+ years, or BS with 8+ years of relevant experience in Computer Science, Computer Engineering, or related field.
  • Hands-on experience developing deep learning–based perception or closely related systems for complex real-world problems, with strong proficiency in PyTorch and production-grade model deployment.
  • Proven experience in data-driven development, including 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 across multidisciplinary teams.

Skills

Required:3D obstacle perceptionmulti-sensor fusiontransformer-based architecturesPyTorchPython
Nice to have:C++

Benefits

  • Equity
  • Benefits (as described by NVIDIA)
Last updated Oct 9, 2026. Interested? Apply on the company site.

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