Senior SLAM and Deep Learning Engineer, Autonomous Vehicles at NVIDIA

Beijing, China

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Autonomous Vehicles, AI, AutomotiveIndustries

Requirements

MS, PhD, or equivalent professional experience in Computer Science, Computer Engineering, Mathematics, Physics, or a related discipline
Over 3 years of relevant industry experience
Expertise in C/C++ programming, with comprehensive understanding of standard C++ features, algorithms, and data structures, along with proficiency in Linux environments
In-depth knowledge of parameter models for sensor calibration
Solid grasp of digital image processing, three-dimensional multi-view geometry, nonlinear optimization, and KF/EKF
Robust mathematical foundation, especially in matrix-related concepts
Engineering expertise in developing and delivering deep learning applications for autonomous vehicles or robotics
Engineering expertise in developing and delivering real-time 3D world models for planning in AV systems
Excellent collaboration skills and ability to work effectively with individuals from various nationalities and locations

Responsibilities

Investigate and resolve sensor calibration and egomotion algorithm/toolchain issues across multiple OEM vehicle platforms
Develop core autonomous driving functionality for global markets by fusing state-of-the-art perception DNNs with map signals
Build real-time 3D world models for planning, integrating diverse inputs from sensors and external sources
Develop and optimize LLM, VLM, and VLA systems for autonomous driving applications, including pre-training and fine-tuning
Design innovative data generation and collection strategies to improve dataset diversity and quality
Collaborate with cross-functional teams to deploy end-to-end AI models in production, ensuring performance, safety, and reliability standards are met
Analyze and resolve sensor calibration and SLAM issues throughout the vehicle delivery process, including triaging and fixing in-platform and online problems with SLAM and sensor calibration for sensors like cameras, radars, lidars, GNSS, IMU, and CAN odometry
Collaborate with the team to design, implement, and deploy advanced end-to-end autonomous driving systems on NVIDIA DRIVE platform in mass-production vehicles

Skills

SLAM

Deep Learning

Sensor Calibration

LiDAR

Radar

Camera

GNSS

IMU

CAN Odometry

LLM

VLM

VLA

Perception DNNs

Egomotion

3D World Models

Autonomous Driving

NVIDIA DRIVE

Pre-training

Fine-tuning

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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