VLA Deep Learning Engineer, End-To-End Autonomous Driving at NVIDIA

Tel Aviv-Yafo, TA, Israel

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Not SpecifiedCompensation

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

Full TimeJob Type

UnknownVisa

Autonomous Driving, AI, RoboticsIndustries

Requirements

PhD or Master's degree with equivalent experience
8+ years of experience
Hands-on experience training LLMs/VLMs/VLAs from scratch, or a proven record as a top-tier ML engineer/researcher passionate about autonomous systems
Strong programming skills in Python and proficiency with major deep learning frameworks
Basic familiarity with C++ for model deployment and integration in safety-critical systems
Comprehensive grasp of current deep learning structures and improvement methods
Consistent track record of deploying production-grade ML models for self-driving, robotics, or related fields at scale

Responsibilities

Build and train innovative large-scale models—including generative, imitation, and reinforcement learning—to improve the planning and reasoning capabilities of driving systems
Explore novel data generation and collection strategies to improve diversity and quality of training datasets
Develop, pre-train, and optimize LLM/VLM/VLA models for autonomous driving and robotics applications
Collaborate cross-functionally to deploy and integrate AI models into vehicle firmware
Deliver production-quality, safety-critical software that meets performance, safety, and reliability standards

Skills

Deep Learning

LLM

VLM

VLA

Generative Models

Imitation Learning

Reinforcement Learning

Autonomous Driving

Model Training

Data Generation

Pre-training

Model Optimization

AI Deployment

Safety-Critical Software

Robotics

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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