Principal On-Device Model Inference Optimization Engineer 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

Technology, AI, AutomotiveIndustries

Requirements

MSc or PhD in Computer Science, Engineering, or a related field, or equivalent experience
Over 10 years of confirmed experience specializing in model inference and optimization
15+ overall years of work experience in a relevant area
Expertise in modern machine learning frameworks, particularly PyTorch, ONNX, and TensorRT
Proven experience in optimizing inference for transformer and convolutional architectures
Strong programming proficiency in CUDA, Python, and C++
In-depth knowledge of optimization techniques, including quantization, pruning, distillation, and hardware-aware neural architecture search
Skilled in building and deploying scalable, cloud-based inference systems
Passionate about developing efficient, production-ready solutions with a strong focus on code quality and performance
Meticulous attention to detail, ensuring precision and reliability in safety-critical systems
Strong collaboration and communication skills for working optimally across multidisciplinary teams
A proactive, diligent mentality with a drive to tackle complex optimization challenges

Responsibilities

Develop and implement strategies to optimize AI model inference for on-device deployment
Employ techniques like pruning, quantization, and knowledge distillation to minimize model size and computational demands
Optimize performance-critical components using CUDA and C++
Collaborate with multi-functional teams to align optimization efforts with hardware capabilities and deployment needs
Benchmark inference performance, identify bottlenecks, and implement solutions
Research and apply innovative methods for inference optimization
Adapt models for diverse hardware platforms and operating systems with varying capabilities
Create tools to validate the accuracy and latency of deployed models at scale with minimal friction
Recommend and implement model architecture changes to improve the accuracy-latency balance

Skills

CUDA

C++

Model Pruning

Quantization

Knowledge Distillation

AI Inference Optimization

Benchmarking

On-Device Deployment

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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