NVIDIA

1 week ago

Senior Radar Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 58 minutes agoStatus: Live

Job Summary

Design and productize NVIDIA’s next-generation autonomous driving radar-based 3D obstacle perception stack. You’ll work on a radar-centric multi-modal obstacle perception pipeline using transformer-based foundation models and multi-sensor fusion (camera, radar, lidar). Own end-to-end architecture, model design, data strategy, KPI/error analysis, and production-grade training and evaluation, while collaborating with safety, systems, and software teams.

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Develop and improve the technical design, architecture, and roadmap for radar-based 3D obstacle perception to support end-to-end autonomous driving functionalities using DNN and transformer-based architectures.
•Conduct applied research to maximize information content of radar point cloud data, addressing low/non-uniform angular resolution, multipath and ghost targets, micro-Doppler signatures, and severe class imbalance.
•Design and implement advanced 3D perception models using radar inputs and multi-sensor fusion (camera, radar, lidar) for obstacle detection, tracking, and BEV scene understanding.
•Drive radar sensor evaluation, selection, and layout optimization to support L2-L4 autonomous driving applications and seamless multi-sensor fusion.
•Build production-grade deep learning models, define objectives, run experiments, maintain KPI frameworks, analyze failure modes, and collaborate on data strategy and auto-labeling workflows.

Pay and Benefits

Salary: USD 224,000 - 356,500 annually

Equity and Bonus:Equity

Key Requirements

•12+ years of hands-on experience developing deep learning-based perception and/or radar signal processing for complex real-world problems, with models taken from prototype to production using frameworks like PyTorch.
•Proven data-driven development experience, including close collaboration with data, labeling, and ground-truth teams for radar data strategy and iterative model improvement.
•Strong programming skills in Python and/or C++, building reliable, high-performance, production-quality software.
•Excellent communication and collaboration skills across multidisciplinary teams spanning AI, hardware, and safety engineering.
•BS/MS/PhD in Computer Science, Electrical Engineering, Robotics, or a related field (or equivalent experience).

Experience:12+ yearsAutonomous drivingDeep learningRadar signal processingMulti-sensor fusion

Education:Bachelor's in Computer Science, Electrical Engineering, Robotics, or related fields

Skills:CommunicationCollaboration

Tech Stack:PyTorchPythonC++TransformersDNNBird’s-Eye-View (BEV) networksLoRACUDACUDA kernelsFMCWBeamformingCFARMicro-DopplerRange-dopplerAzimuth-elevationLidar-to-radar

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

1 week ago

Senior Radar Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 58 minutes agoStatus: Live

Job Summary

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Develop and improve the technical design, architecture, and roadmap for radar-based 3D obstacle perception to support end-to-end autonomous driving functionalities using DNN and transformer-based architectures.
•Conduct applied research to maximize information content of radar point cloud data, addressing low/non-uniform angular resolution, multipath and ghost targets, micro-Doppler signatures, and severe class imbalance.
•Design and implement advanced 3D perception models using radar inputs and multi-sensor fusion (camera, radar, lidar) for obstacle detection, tracking, and BEV scene understanding.
•Drive radar sensor evaluation, selection, and layout optimization to support L2-L4 autonomous driving applications and seamless multi-sensor fusion.
•Build production-grade deep learning models, define objectives, run experiments, maintain KPI frameworks, analyze failure modes, and collaborate on data strategy and auto-labeling workflows.

Pay and Benefits

Salary: USD 224,000 - 356,500 annually

Equity and Bonus:Equity

Key Requirements

•12+ years of hands-on experience developing deep learning-based perception and/or radar signal processing for complex real-world problems, with models taken from prototype to production using frameworks like PyTorch.
•Proven data-driven development experience, including close collaboration with data, labeling, and ground-truth teams for radar data strategy and iterative model improvement.
•Strong programming skills in Python and/or C++, building reliable, high-performance, production-quality software.
•Excellent communication and collaboration skills across multidisciplinary teams spanning AI, hardware, and safety engineering.
•BS/MS/PhD in Computer Science, Electrical Engineering, Robotics, or a related field (or equivalent experience).

Experience:12+ yearsAutonomous drivingDeep learningRadar signal processingMulti-sensor fusion

Education:Bachelor's in Computer Science, Electrical Engineering, Robotics, or related fields

Skills:CommunicationCollaboration

Tech Stack:PyTorchPythonC++TransformersDNNBird’s-Eye-View (BEV) networksLoRACUDACUDA kernelsFMCWBeamformingCFARMicro-DopplerRange-dopplerAzimuth-elevationLidar-to-radar

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor