Senior Solutions Architect, Generative AI at NVIDIA

Mumbai, Maharashtra, India

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Not SpecifiedCompensation

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

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience
5+ years of hands-on experience in a technical role, specifically focusing on generative AI, with a strong emphasis on training Large Language Models (LLMs)
Proven track record of successfully deploying and optimizing LLM models for inference in production environments
In-depth understanding of state-of-the-art language models, including but not limited to GPT-3, BERT, or similar architectures
Expertise in training and fine-tuning LLMs using popular frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers
Proficiency in model deployment and optimization techniques for efficient inference on various hardware platforms, with a focus on GPUs
Strong knowledge of GPU cluster architecture and the ability to leverage parallel processing for accelerated model training and inference
Excellent communication and collaboration skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders
Experience leading workshops, training sessions, and presenting technical solutions to diverse audiences

Responsibilities

Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows
Collaborate closely with customers to understand their language-related business challenges and design tailored solutions
Collaborate with sales and business development teams to support pre-sales activities, including technical presentations and demonstrations of LLM and RAG capabilities
Work closely with NVIDIA engineering teams to provide feedback and contribute to the evolution of generative AI technologies
Engage directly with customers to understand their language-related requirements and challenges
Lead workshops and design sessions to define and refine generative AI solutions focused on LLMs and RAG workflows
Lead the training and optimization of Large Language Models using NVIDIA’s hardware and software platforms
Implement strategies for efficient and effective training of LLMs to achieve optimal performance
Design and implement RAG-based workflows to enhance content generation and information retrieval
Work closely with customers to integrate RAG workflows into their applications and systems
Stay abreast of the latest developments in language models and generative AI technologies
Provide technical leadership and guidance on best practices for training LLMs and implementing RAG-based solutions

Skills

Key technologies and capabilities for this role

LLMsRAGGenerative AILarge Language ModelsRetrieval-Augmented GenerationModel TrainingModel OptimizationNVIDIA HardwareNVIDIA SoftwareAI Solutions Architecture

Questions & Answers

Common questions about this position

What education and experience are required for this Senior Solutions Architect role?

A Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience is required, along with 5+ years of hands-on experience in generative AI focusing on training Large Language Models (LLMs), and a proven track record of deploying and optimizing LLMs in production.

What key technical skills are needed for this position?

Expertise in training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers is required, along with in-depth understanding of language models such as GPT-3 or BERT, proficiency in model deployment and optimization on GPUs, and strong knowledge of GPU cluster architecture.

Is this a remote position, or is there a location requirement?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What soft skills are important for success in this role?

Excellent communication and collaboration skills are essential, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders, and experience collaborating with customers, sales teams, and engineering teams.

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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