[Remote] Senior Deep Learning Engineer, Visual Generative AI at NVIDIA

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Computer Hardware, Software DevelopmentIndustries

Skills

Key technologies and capabilities for this role

Deep LearningDiffusion ModelsVision-Language Models (VLMs)Model OptimizationInference OptimizationGPU PlatformsVisual Generative AITensorRTTensorRT-LLMvLLMPythonPyTorchTransformer ArchitecturesAttention MechanismsU-NetDiTLow-latency inferenceHigh-throughput inferenceSoftware Development

Questions & Answers

Common questions about this position

What experience and education are required for this Senior Deep Learning Engineer role?

Candidates need 3+ years of experience in DL model implementation and SW Development, along with a BSc, MS or PhD in Computer Science, Computer Architecture or related field.

What key technical skills are essential for this position?

Required skills include extensive knowledge of at least one DL Framework with practical experience in PyTorch, deep understanding of transformer architectures and Visual Generative AI models like U-Net and DiT, excellent Python programming, strong problem-solving, DL fundamentals, and Docker basics.

What is the compensation or salary for this role?

This information is not specified in the job description.

Is this position remote or does it require working in an office?

This information is not specified in the job description.

What makes a candidate stand out for this Senior DL Algorithms Engineer position?

Stand out with experience in performance measurements and profiling, hands-on work with model optimization frameworks like TensorRT, TensorRT-LLM, vLLM, deep understanding of distributed systems for large-scale inference, experience extending open-source tools for Visual Generative AI, and familiarity with latest trends in the field.

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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