Senior Perception 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

Automotive, Artificial Intelligence, TechnologyIndustries

Requirements

2+ years of technical leadership demonstrating high technical and organizational complexity
12+ 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 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)
Ways to stand out
Proven expertise in developing perception solutions for autonomous driving or robotics using deep learning with cameras
Hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real time applications
Proven expertise in deep learning backed up by technical publications in leading conferences/journals
Good understanding of fundamentals of 3D computer vision, camera calibrations including intrinsic and extrinsic
Experience with development in CUDA language. The ability to implement CUDA kernels as part of training or inference pipelines

Responsibilities

Designing end-to-end solutions for Perception and AV stack to enable wait condition and fine grained classification tasks in complex driving environments (e.g., traffic light, traffic signs, roadmarks, texts, classes of dynamic objects, and vehicles’ light signals such as brake, turn, hazard etc.)
Applied research and development of innovative deep learning models
Develop localization and tracking algorithms to improve output accuracy of detection and classification solutions under challenging and diverse scenarios
Develop generalizable approaches to support ODD and Country/region expansion
Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness
Drive and prioritize data-driven development by working with large data collection and labeling teams to bring in high value data to improve perception system accuracy, including data collection prioritization and planning, labeling prioritization, labeling efficiency optimization

Skills

Deep Learning

Computer Vision

Object Detection

Object Tracking

Localization

Perception Systems

Autonomous Driving

GPU Computing

Neural Networks

Data Labeling

Semantic Segmentation

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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