Senior AI Tools Engineer, SRE Operations - GeForce NOW

NVIDIA•Santa Clara, CA

8d•$144,000 - $230,000

About The Position

NVIDIA is seeking an AI Tools Engineer to join the Site Reliability Engineering (SRE) Data Team supporting GeForce NOW. The role builds and deploys AI-powered tools and products that help operate and optimize a critical global production service. It transforms production signals, metrics, logs, and other data streams into actionable intelligence to automate incident root-cause analysis and predict service trends and patterns. The engineer will develop AI/ML tools and new LLM- and agent-based systems, manage large-scale data pipelines and LLM-based pipelines, and guide technical decisions about AI frameworks, platforms, tools, and architectures to support the product’s long-term technical sustainability. Applicants with SRE or equivalent experience are encouraged.

Requirements

Bachelor’s degree in Computer Science, Statistics, or Engineering, or equivalent experience.
At least 5 years of experience.
Strong proficiency in Python.
Practical experience building, optimizing, and deploying AI tools.
Strong knowledge of AI and current developments, including how LLM-based platforms are built and optimized and which platforms are appropriate.
Hands-on experience with Kubernetes and AWS cloud environments.
Ability to assess AI developments and distinguish meaningful advances from noise when making technical decisions.
Expertise in automation and large-scale data pipelines.
Experience using monitoring and visualization tools such as Grafana to interact with data.
Ability to handle data sources and pipelines to transform and manage data.

Nice To Haves

Familiarity with Go or other systems languages.
Understanding of SRE principles and experience managing production environments.
Experience with LLM improvement pipelines and a strong understanding of recent developments in LLM training.
In-depth knowledge of LLMs and AI models, with the ability to recommend an approach that supports the long-term needs of the team and product and avoids unsuitable platform choices.
Experience with Kubernetes, AWS, and other cloud technologies.
Proficiency in automation.

Responsibilities

Build and implement AI/ML tools that analyze production data to identify root causes of complex incidents and forecast operational trends.
Lead development of new LLM- and agent-based systems to improve operational efficiency.
Establish and maintain data management practices, including pipelines for transforming and handling large-scale data sources used in model development.
Take charge of and enhance LLM-based pipelines, incorporating knowledge of LLM developments into product development.
Advise on AI frameworks, platforms, toolsets, and architecture to support the product’s long-term technical sustainability.