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高级AI工作流工程师

雇主

NVIDIA

地点

Santa Clara · 美国

待遇

$面议

工作模式

线下

截止日期

1月10日

福利
Equity,Benefits

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岗位摘要

Senior engineer to design and implement AI-driven tools and agentic AI solutions that automate end-t

岗位职责

Today,
NVIDIA is tapping into the unlimited potential of AI to define the next era of computing.
An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world.
Doing what’s never been done before takes vision, innovation, and the world’s best talent.
As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work.
Come join the team and see how we can make a lasting impact on the world.
NVIDIA is hiring senior software engineers in its Infrastructure, Planning and Process Team (IPP), to accelerate AI adoption across various engineering workflows within the company.
IPP is a global organization within
NVIDIA.
The group works with various other teams within
NVIDIA such as Graphics Processors, Mobile Processors, Deep Learning, Artificial Intelligence and Driverless Cars to cater to their infrastructure and software development workflow needs.
As a senior engineer on AI Workflow, you will design and implement tools and software solutions that leverage Large Language Models and agentic AI to automate end to end software engineering workflows and enhance the productivity of engineers across
NVIDIA.
What you’ll be doing:
• Design and implement AI-driven optimizations within software development workflows to enhance developer productivity, accelerate feedback loops, and improve release reliability.
• Experience designing, developing, and deploying AI agents to automate and software development workflows and processes.
• Continuously measure and report on the impact of AI interventions, demonstrating improvements in key metrics like cycle time, change failure rate, and mean time to recovery (MTTR).
• Create and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures.
• Conduct research on emerging technologies to recommend best practices and improvements What we need to see:
• BE (MS preferred) or equivalent experience in
EE/CS with 10
years of work experience.
• Well versed with Large Language Mode (LLM), Machine Learning (ML), Agentic AI techniques.
• Hands-on experience in using large language models (LLMs) and implementing AI for software engineering workflows.
• Hands-on experience on Python/Java/Go with extensive python scripting experience.
• Experience in working with SQL/NoSQL database systems such as MySQL, MongoDB or Elasticsearch.
• Experience in Full stack development..
Proficient in front-end (e.g., React, Angular, Vue.js, HTML, CSS, JavaScript), back-end (e.g., Node.js, Python/Django/Flask, Ruby on Rails, Java/Spring, .NET) development, database management (SQL/NoSQL), and deployment/hosting (e.g., AWS, Azure, GCP).
• Experience with tools for
CI/CD setup such as Jenkins, Gitlab CI, Packer, Terraform, Artifactory, Ansible, Chef or similar tools.
• Good understanding of distributed systems, understanding of microservice architecture and
REST APIs.
• Good to have knowledge of build tools like Make, Maven or Ant.
• Ability to effectively work across organizational boundaries to enhance alignment and productivity between teams.
Ways to stand out from the crowd:
• Proactively track AI tool and technology trends, build insights, and collaborate with development teams early to evangelize AI driven workflows
NVIDIA adoption.
• We have some of the most forward-thinking and versatile people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing.
We are building a team that will truly change the world.
If you are passionate about new technologies, care about software quality, and want to be part of the future of transportation and AI, I would love for you to join us.
• Expertise in leveraging large language models (LLMs) and Agentic AI to automate complex workflows, with knowledge of retrieval-augmented generation(RAG) and fine-tuning LLMs on enterprise data.
• Prior development of a large software project using service oriented architecture operating with real time constraints We have some of the most forward-thinking and versatile people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing.
We are building a team that will truly change the world.
If you are passionate about new technologies, care about software quality, and want to be part of the future of transportation and AI, we would love for you to join us.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits. Applications for this job will be accepted at least until August 9, 2026.
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.

申请条件

BE (MS preferred) or equivalent experience in EE/CS with 10+ years of work experience.
Well versed with Large Language Models (LLM), Machine Learning (ML), and Agentic AI techniques.
Hands-on experience in using large language models (LLMs) and implementing AI for software engineering workflows.

雇主简介

NVIDIA is a technology company that designs GPUs and system-on-chip units for gaming, professional visualization, data centers, and automotive markets. The Physics Simulation Team focuses on physics simulation for robotics learning and evaluation.

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