Parking Perception DNN Engineer at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Autonomous Driving, Artificial IntelligenceIndustries

Requirements

10+ years of hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch)
Experience in multi-sensor fusion (cameras, ultrasonic sensors, radar) for perception tasks, particularly in high-resolution world reconstruction
Proven experience in production deep learning model development, including careful data verification, model architecture design, loss function engineering, and debugging ML models
Experience in data-driven development and collaboration with data and ground truth teams
Strong programming skills in python and/or C++
Outstanding communication and teamwork skills
BS/MS/PhD in CS, EE, sciences or related fields (or equivalent experience)

Responsibilities

Develop multi-sensor fusion based deep learning model development for obstacle perception/fusion in complex driving environments
Conduct applied research and development of innovative deep learning and multi-sensor fusion algorithms to improve output accuracy of 3D obstacle perception solutions under challenging and diverse scenarios, with a focus on high-resolution world reconstruction (e.g., occupancy networks)
Identify and analyze the strength and weakness of the developed 3D obstacle perception solutions using large scale benchmark data (both real and synthetic) and improve them iteratively through KPI building and optimization, including data verification, model architecture design, loss function engineering, and debugging ML bugs
Productize the developed 3D obstacle perception solutions by meeting product requirements for safety, latency, and SW robustness, with emphasis on production deep learning model development
Drive and prioritize data-driven development by working with large data collection and labeling teams, including data collection prioritization and planning, labeling prioritization to maximize data value

Skills

Deep Learning

DNN

Multi-Sensor Fusion

3D Perception

Occupancy Networks

Camera Sensors

Ultrasonic Sensors

Radar

Model Architecture

Loss Function Engineering

KPI Optimization

Benchmark Analysis

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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