Principal Perception Engineer – Obstacle Foundation Models, Autonomous Vehicles

NVIDIA

. Own the technical vision, architecture, and roadmap for 3D obstacle perception supporting end-to-end autonomous driving .

Posted 10/2/2026full-timeRemote • California • United StatesLead💰 $272,000 - $431,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying deep learning models for 3D perception in autonomous driving, with a strong focus on technical leadership, data-driven development, and collaboration across multidisciplinary teams.

Highest-signal resume keywords

Deep Learning Model Development3D Perception SystemsTechnical LeadershipData-Driven DevelopmentPython Programming

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Deep Learning3D Computer VisionCamera ModelingMulti-View GeometryCUDA DevelopmentDNN-Based Perception PipelinesModel OptimizationSensor FusionKPI FrameworksProduction-Grade Software

Soft Skills

Excellent CommunicationCollaboration SkillsMentorship

Tools & Technologies

PyTorchGPU AccelerationCamera SensorsRadar SensorsLidar Sensors

Certifications & Qualifications

BS/MS/PhD in Computer ScienceElectrical Engineering

Industry Keywords

Autonomous DrivingRoboticsPerception SolutionsComputer VisionVision-Language Models

Tech Stack

Tools & technologies

PythonPyTorchC++

About the role

Key responsibilities & impact

Own the technical vision, architecture, and roadmap for 3D obstacle perception supporting end-to-end autonomous driving
Design and develop 3D perception models using multi-camera inputs and/or camera, radar, and lidar sensor fusion
Lead development of efficient, production-grade deep learning models
Define objectives, select architectures, guide experimentation, and establish training and evaluation best practices
Define and drive KPI frameworks for perception performance
Analyze large-scale real and synthetic datasets to identify failure modes and improve accuracy, robustness, and efficiency
Lead perception data strategy, including data and labeling requirements, collection, annotation, active learning, auto-labeling, VLMs, and model-in-the-loop tooling
Partner with safety, systems, and software teams to meet product requirements for safety, latency, resource usage, and software robustness
Drive deployment readiness at scale
Provide technical leadership and mentorship across perception and autonomy teams

Requirements

What you’ll need

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
Track record of taking models from prototype to production
Demonstrated technical leadership as a senior or principal-level individual contributor
Experience owning features or subsystems end-to-end, setting technical direction, making architectural decisions, and coordinating across teams
Proven experience in data-driven development, including collaboration with data, labeling, and ground-truth teams
Strong programming skills in Python and/or C++
History of building reliable, high-performance, production-quality software
Excellent communication and collaboration skills
BS/MS/PhD in Computer Science, Electrical Engineering, or related fields, or equivalent experience
Experience leading 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
Experience optimizing latency, memory, and compute constraints
Familiarity with CNNs, transformers, large-scale pretraining, parameter-efficient fine-tuning such as LoRA, and vision-language models
Strong publication record or recognized contributions in deep learning, computer vision, or autonomous systems
Deep understanding of 3D computer vision, camera modeling and calibration, multi-view geometry, and 3D representations
Experience with CUDA development and GPU-accelerated components

Benefits

Comp & perks

Equity
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