[Remote] Multimodal Deep Learning Solution Architect - Vision Language and Action Models at NVIDIA

France

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Not SpecifiedCompensation

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

Full TimeJob Type

UnknownVisa

Robotics, Manufacturing, HealthcareIndustries

Requirements

MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields
Deep expertise in AI/Deep Learning, with hands-on experience in training or optimizing VLMs for production
Expertise with deep learning frameworks for training VLMs (PyTorch, Nemo), and/or experience with such model's optimization methods and tools (TensorRT and Triton Inference Server)
Excellent verbal, written communication, and technical presentation skills in English
5+ years' work or research experience with Python/C++/other software development
AI passionate with a growth mindset, ability to collaborate effectively with different teams (Engineering, Product, Sales, Marketing) in a rapidly evolving environment while continuously learning and sharing insights

Responsibilities

Serve as the primary technical expert between NVIDIA and customers, understanding their technology and providing the best AI solutions/guidance on training processes in terms of tools and methodology
Build proof-of-concepts and demonstrations that highlight the power of NVIDIA AI platforms for Vision Language Reasoning Models
Partner with developers, researchers, technology specialists, IT professionals, and executives to facilitate the integration of NVIDIA technology
Partner with Engineering, Product, and Sales teams to develop and plan best suitable solutions for customers
Enable development and growth of product features through customer feedback and proof-of-concept evaluations

Skills

Key technologies and capabilities for this role

Multimodal Deep LearningVision-Language ModelsReinforcement LearningSupervised Fine-TuningNeural Network OptimizationLarge-Scale PretrainingData CurationNVIDIA AI PlatformsPhysical AIRoboticsAutonomous Systems

Questions & Answers

Common questions about this position

What education is required for this Solutions Architect role?

A MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields is required.

What technical expertise is needed for this position?

Deep expertise in AI/Deep Learning with hands-on experience in training or optimizing VLMs for production, expertise with deep learning frameworks like PyTorch and Nemo, and experience with optimization tools like TensorRT and Triton Inference Server are required. Additionally, 5+ years of work or research experience with Python/C++/other software development is needed.

What soft skills are important for this role?

Excellent verbal, written communication, and technical presentation skills in English, along with a growth mindset and ability to collaborate effectively with different teams in a rapidly evolving environment, are essential.

What kind of collaboration is involved in this position?

You will partner with developers, researchers, technology specialists, IT professionals, executives, Engineering, Product, and Sales teams to develop solutions, integrate NVIDIA technology, and enable product growth through customer feedback.

What makes a strong candidate for this Solutions Architect role?

Candidates with deep expertise in VLMs, hands-on experience training models for production, proficiency in PyTorch/Nemo and optimization tools, strong communication skills, and a collaborative growth mindset in a fast-paced environment stand out.

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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