We are seeking an AI Engineer to design and build intelligent systems that transform how we do customer support. Our organization processes large amounts of data from various sources, such as customers, end users, and web and social media platforms. This role focuses on using Generative AI, large language models (LLMs), and RAG-based systems to transform fragmented data into actionable insights. It also automates reporting and allows teams to engage with data in completely new ways.
One project within this role includes modernizing our localization workflows using AI, but the main focus is developing scalable tools that boost efficiency, increase visibility, and support decision-making across the organization.
What You’ll Be Doing:
Build and develop AI-powered tools that improve workflow efficiency, data analysis, and decision-making across customer support
Build systems that ingest and unify data from multiple sources (internal databases, forums, social media, internal tools)
Develop LLM- and RAG-based solutions that allow users to query systems in natural language and retrieve detailed, contextual insights
Build automated reporting and metrics generation tools tailored to different collaborators (engineering, QA, program management, customers, support teams)
Enable personalized, role-based data access—allowing individuals and teams to easily retrieve the information most relevant to them
Identify patterns, trends, and root causes from internal systems using advanced analytical methods
Lead the development of AI-assisted localization pipelines to improve translation speed and scalability and targeted human translation
Research, evaluate, and implement emerging AI technologies to continuously improve internal systems
Provide technical leadership and guidelines for AI-based system build and deployment
What We Need to See:
BS or MS in Computer Science, Artificial Intelligence, or equivalent experience
8+ years of experience in Machine Learning, Natural Language Processing, or related AI domains
Deep understanding of large language models (LLMs) and strong experience crafting and implementing RAG-based workflows
Strong programming skills with extensive experience in Python
Experience building production-grade AI systems, APIs, or data pipelines
Experience working with large, complex datasets and building analytical or reporting systems
Strong problem-solving skills, performance analysis experience, and debugging expertise
Solid foundation in algorithms and mathematical principles
Experience with source control tools such as Git or Perforce
Ability to work independently and collaboratively across teams
Ways to Stand Out from the Crowd:
Experience building analytics platforms or internal tools for data exploration using advanced technologies
Experience applying AI to customer support, bug tracking, or large-scale feedback systems
Familiarity with knowledge retrieval systems, embeddings, and semantic search
Experience with real-time or near-real-time data processing pipelines
Background in localization, translation systems, or multilingual AI workflows
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- BS or MS in Computer Science, Artificial Intelligence, or equivalent experience
- 8+ years of experience in Machine Learning, NLP, or related AI domains
- Deep understanding of large language models (LLMs) and RAG-based workflows
- Strong programming skills with extensive experience in Python
- Experience building production-grade AI systems, APIs, or data pipelines
- Experience working with large, complex datasets and building analytical or reporting systems
- Strong problem-solving, performance analysis, and debugging expertise
- Solid foundation in algorithms and mathematical principles
- Experience with source control tools such as Git or Perforce
- Ability to work independently and collaboratively across teams
- Experience building analytics platforms or internal data-exploration tools
- Experience applying AI to customer support, bug tracking, or large-scale feedback systems
- Familiarity with knowledge retrieval systems, embeddings, and semantic search
- Experience with real-time or near-real-time data processing pipelines
- Background in localization, translation systems, or multilingual AI workflows
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
