Senior AI Tools Engineer, SRE Operations - GeForce NOW

NVIDIA•Santa Clara, CA

1d•$144,000 - $230,000

About The Position

NVIDIA is seeking a passionate AI Tools Engineer to join the Site Reliability Engineering (SRE) Data Team. This role is critical for transforming extensive production data streams—such as signals, metrics, and logs—into actionable intelligence. The intelligence automates root cause analysis for incidents and predicts future service trends and patterns. You will build and deploy sophisticated AI-powered tools and products that support the operation and optimization of a critical production global Geforce Now service.

Requirements

B.S. in Computer Science, Statistics, or Engineering (or equivalent experience), and 5+ years of experience.
Strong proficiency in Python; familiarity with Go or other systems languages is a plus.
Practical experience building, optimizing, and deploying AI tools.
Strong knowledge of the AI space and current developments, including understanding how LLM-based platforms are built, optimized, and which platforms work best.
Hands-on experience with container orchestration (Kubernetes) and cloud environments (AWS cloud).
Active engagement with developments in the AI field and the ability to distinguish meaningful advances from noise when making technical decisions.
Expertise in automation and handling large-scale data pipelines.
Experience applying monitoring and visualization tools, such as Grafana, to interact with data.
Excellent ability to handle data sources and pipelines to transform and manage data.

Nice To Haves

Understanding of SRE principles and experience managing production environments.
Strong in LLM improvement pipelines as well as a strong grasp of recent developments in LLM training.
Someone with excellent knowledge of LLMs and AI Models who can reason and recommend an approach that sustains the team and product long term.
This person helps prevent grave mistakes by avoiding the wrong platform choice.
Understanding of SRE concepts and managing production environments as well as experience with Kubernetes, AWS, and other cloud technologies.
Proficiency in automation.

Responsibilities

Build and implement robust AI/ML tools capable of analyzing production data to identify root causes for complex incidents and identify future operational trends.
Lead the development of brand-new LLM- and Agent-based systems to improve operational efficiency.
Establish and maintain excellent data management practices, including building pipelines to transform and handle large-scale data sources vital for model development.
Take charge of and enhance LLM-based pipelines while integrating a strong grasp of LLM progress into product development.
Act as a resident authority on AI Frameworks, recommending the best platforms, toolsets, and architectural approaches to ensure the long-term technical sustainability of the product.