NVIDIA Corporation

Senior Radar Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles

NVIDIA Corporation • $224K — $356K *
Santa Clara, CA 95051In-Person
Transportation
11 - 15 years of experience
Today
Be an Early Applicant
Job Overview by Ladders

Qualifications

  • 12+ years of experience in deep learning-based perception or radar signal processing for complex real-world applications.
  • Proficiency in frameworks like PyTorch and experience from prototype to production.
  • Strong programming skills in Python and/or C++ with a focus on high-performance software.
  • Proven experience in data-driven development and collaboration with data teams.
  • BS/MS/PhD in Computer Science, Electrical Engineering, Robotics, or equivalent experience.

Responsibilities

  • Develop and enhance radar-based 3D obstacle perception architecture.
  • Conduct applied research to improve radar point cloud data representation.
  • Design and implement advanced multi-sensor 3D perception models for obstacle detection.
  • Drive radar sensor evaluation and layout optimization for autonomous driving.
  • Build efficient production-grade deep learning models following best practices.
  • Define and maintain KPI frameworks to evaluate radar perception performance.
  • Contribute to the data strategy for radar perception including data collection and model-assisted workflows.
  • Collaborate with cross-functional teams to meet product safety and robustness requirements.

Benefits

  • Equity eligibility in addition to salary.
  • Access to a variety of employee benefits.
Full Job Description
We are seeking an exceptional Senior Radar Perception Engineer to help design and productize NVIDIA's next-generation autonomous driving perception stack. You will work on the core 3D radar and multi-modal obstacle perception pipeline, contribute to architecture and algorithm design, and remain deeply hands-on with implementation, including modern transformer-based, radar-centric foundation models, and multi-sensor fusion techniques where they add real value.

What you'll be doing:
  • Architecture & Roadmap: Develop and improve the technical design, architecture, and roadmap for radar-based 3D obstacle perception to support end-to-end autonomous driving functionalities, leveraging state-of-the-art DNN and transformer-based architectures.
  • Radar Perception Innovation: Conduct applied research on deep learning models to maximize the information content of radar point cloud data at every representation level. Tackle radar perception's hardest problems: low and non-uniform angular resolution, multipath and ghost targets, micro-doppler signatures for small targets, and severe class imbalance. Explore weakly-supervised pretraining and improve radar perception via large auto-labeled datasets.
  • Model Design & Fusion: Design and implement advanced 3D perception models utilizing radar inputs (ranging from low-level range-doppler/azimuth-elevation maps to sparse/dense point clouds) and multi-sensor fusion (camera, radar, lidar) for obstacle detection, tracking, and Bird's-Eye-View (BEV) scene understanding.
  • Sensor & Stack Integration: Drive radar sensor evaluation, selection, and layout optimization to support L2-L4 autonomous driving applications, ensuring seamless multi-sensor fusion.
  • Production Deep Learning: 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 radar pretraining, cross-modal distillation (e.g., lidar-to-radar), and parameter-efficient fine-tuning (e.g., LoRA).
  • KPIs & Error Analysis: Help define and maintain KPI frameworks to quantify radar perception performance; analyze large-scale real and synthetic datasets to identify failure modes unique to radar (e.g., multipath reflections, clutter, ghost objects) and systematically improve accuracy, robustness, and efficiency.
  • Data Strategy & Auto-Labeling: Contribute to the data strategy for radar perception: specify data and labeling requirements, help prioritize data collection and annotation, and collaborate with data and ground-truth teams, incorporating model-assisted workflows (e.g., active learning, automated radar labeling via lidar/camera foundation models) and model-in-the-loop tooling.
  • Cross-Functional Productization: Collaborate with safety, systems, and software teams to ensure radar perception solutions meet product requirements for safety, low latency, resource usage, and software robustness, and are ready for deployment at scale.


What we need to see:
  • Industry Experience: 12+ years of hands-on experience developing deep learning-based perception, radar signal processing, 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.
  • Data-Driven Workflows: Proven experience in data-driven development, including close collaboration with data, labeling, and ground-truth teams on radar data strategy, labeling quality, and iterative model improvement.
  • Software Engineering: Strong programming skills in Python and/or C++, with experience building reliable, high-performance, production-quality software.
  • Collaboration: Excellent communication and collaboration skills, with the ability to work effectively across multidisciplinary teams spanning AI, hardware, and safety engineering.
  • Education: BS/MS/PhD in Computer Science, Electrical Engineering, Robotics, or related fields (or equivalent experience).


Ways to stand out from the crowd:
  • Radar & Multi-Modal Scale: Experience designing and deploying radar-based or multi-modal perception solutions for autonomous driving or robotics using deep learning at scale.
  • Embedded Optimization: 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 familiarity with modern architectures (e.g., Transformers, BEV networks).
  • Signal Processing Depth: Deep understanding of radar physics and digital signal processing fundamentals (FMCW, beamforming, CFAR, micro-Doppler) and how to cleanly interface traditional signal processing outputs with downstream deep learning models.
  • Academic/Research Track Record: Strong publication record or recognized contributions in deep learning, radar perception, multi-sensor fusion, or autonomous systems at leading conferences/journals (e.g., CVPR, ICCV, NeurIPS, IROS).
  • GPU Acceleration: Experience with CUDA development and optimizing training or inference pipelines through custom CUDA kernels or other GPU-accelerated components to handle high-bandwidth raw radar or tensor data.


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

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 19, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Manufacturing & Automotive
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ
NVDA
* Ladders Estimates

Similar Jobs

Ad banner background

Get Ready For Your
Next Interview

More Jobs at NVIDIA Corporation

More Transportation Jobs

Find similar Senior Radar Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles jobs:

NationwideSanta Clara, CA