Product Technical Lead, GenAI at NVIDIA

Santa Clara, California, United States

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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

7+ years of proven experience in technical Product or Engineering roles in Enterprise Software, Cloud Platforms, and production deployments with a focus on building partner integrations
Masters or PhD in Computer Science, Electrical Engineering or equivalent experience
Strong background in AI/ML and Deep Learning with hands-on knowledge of Generative AI frameworks and Programming languages such as Python, PyTorch, NVIDIA NeMo, Hugging Face, LangChain, JAX, etc., with a proven track record of building enterprise-grade GenAI systems such as RAGs and Agents
Strong understanding of Enterprise IT environments including Security, Compliance, Governance, Data infrastructure, and Deployment across on-prem, hybrid, and multi-cloud platforms
Understanding of MLOps lifecycle, container orchestration, and Cloud Native technologies including Kubernetes, Docker, Kubeflow, and Cloud Service Integrations with AWS, Azure, GCP and related technologies
Strong systems thinking, ability to lead through undefined problems, and a deep curiosity for emerging AI technologies
Strong sense of ownership, initiative, and leading projects end-to-end

Responsibilities

Architect integration of Generative AI offerings within ISV Software Platforms, driving close relationship with ISV Platform Architects
Define technical objectives, timelines, and technical adoption strategy, aligning with their long-term business objectives
Lead the technical product engagement, serving as their primary point of contact
Drive regular cadence meetings, progress tracking, adoption status, and regular internal reporting consistent with NVIDIA's culture
Collaborate with NVIDIA Product, Engineering, Research, Solution Architecture, and other organizations to arrive at the most promising solution
Represent Partner needs, constraints, and architecture design to Product and Engineering teams
Contribute to Product roadmap by synthesizing findings from large-scale enterprise environments and cross-industry patterns, captured from ISV engagements
Showcase methodologies for designing scalable GenAI Platforms across stages such as Data Curation and Ingestion, Retrieval-Augmented Generation (RAG), Model Finetuning and Alignment, Agentic workflows and production-ready deployments as it relates to ISV and CSP Integrations
Develop expertise in GenAI Platform Architecture and keep up to date with the latest in the industry and NVIDIA offerings, including NIMs, NeMo Microservices, NVIDIA OSS Software and Frameworks and Product updates to best support the customer Platform teams

Skills

Key technologies and capabilities for this role

Generative AIRAGModel FinetuningAgentic AIData CurationData IngestionPlatform ArchitectureProduct StrategyTechnical LeadershipISV Integration

Questions & Answers

Common questions about this position

What experience level is required for this Product Technical Lead role?

The role requires 7+ years of proven experience in technical Product or Engineering roles in Enterprise Software, Cloud Platforms, and production deployments with a focus on building partner integrations.

What education is needed for this position?

A Masters or PhD in Computer Science, Electrical Engineering or equivalent experience is required.

What technical skills are essential for this GenAI role?

Candidates need a strong background in AI/ML and Deep Learning, hands-on knowledge of Generative AI frameworks and programming languages such as Python, PyTorch, NVIDIA NeMo, Hugging Face, LangChain, JAX, and a proven track record of building enterprise-grade GenAI systems like RAGs and Agents.

What is the salary or compensation for this position?

This information is not specified in the job description.

Is this role remote or does it require office presence?

This information is not specified in the job description.

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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