英伟达Senior AI Engineer, Agents and Developer Workflows
任职要求
• BE (MS preferred) or equivalent experience in EE/CS with 10+ years of work experience. • Deep practical knowledge of Large Language Models (LLMs), Machine Learning (ML), and Agent development • Strong background in implementing AI solutions to solve real-world software engineering problems. • 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. • Full-stack, end-to-end development expertise, with proficiency in building and integrating solutions from the front-end (e.g., React, Angular) to the back-end (Python, Go, Java) and managing data infrastructure (SQL/NoSQL). • 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. • Ability to effectively work across organizational boundaries to enhance alignment and productivity between teams. Ways to stand out from the crowd: • Proven expertise in applied AI, particularly using Retrieval-Augmented Generation (RAG) and fine-tuning LLMs on enterprise data to solve complex software engineering challenges. • Experience delivering large-scale, service-oriented software projects under real-time constraints, demonstrating an understanding of the complex development environments this role will optimize. • 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. 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.
工作职责
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 create and establish 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: • Develop and implement solutions throughout software development lifecycles to improve developer efficiency, accelerate feedback loops, and boost release reliability • Experience designing, developing, and deploying AI agents to automate software development workflows and processes. • Continuously measure and report on the impact of AI interventions, showing progress in metrics such as cycle time, change failure rate, and mean time to recovery (MTTR). • Build and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures. • Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge.
• Design, develop, and deploy robust AI/ML systems with high-quality, scalable, and maintainable code • Translate complex, ambiguous requirements into clear technical plans and lead project execution across engineering efforts • Build scalable infrastructure and platforms to support cutting-edge machine learning workflows, including agentic systems that can plan, reason, and act autonomously • Research and apply state-of-the-art ML techniques—including LLMs, custom model training, and RAG/agent-based architectures—to real-world hardware challenges • Stay current with the fast-evolving AI/ML landscape, continuously improving our tools, systems, and methods to maintain a technical edge • Provide technical mentorship, foster a culture of excellence and inclusion, and help grow team capabilities • Lead design discussions, author technical documentation, and provide thoughtful, actionable feedback to peers • Represent the team in executive reviews, product demos, retrospectives, and cross-functional forums
• Design and implement end-to-end data pipelines (ETL) to ensure efficient data collection, cleansing, transformation, and storage, supporting both real-time and offline analytics needs. • Develop automated data monitoring tools and interactive dashboards to enhance business teams’ insights into core metrics (e.g., user behavior, AI model performance). • Collaborate with cross-functional teams (e.g., Product, Operations, Tech) to align data logic, integrate multi-source data (e.g., user behavior, transaction logs, AI outputs), and build a unified data layer. • Establish data standardization and governance policies to ensure consistency, accuracy, and compliance. • Provide structured data inputs for AI model training and inference (e.g., LLM applications, recommendation systems), optimizing feature engineering workflows. • Explore innovative AI-data integration use cases (e.g., embedding AI-generated insights into BI tools). • Provide technical guidance and best practice on data architecture that meets both traditional reporting purpose and modern AI Agent requirements.
• Core Development & Optimization: Participate in the development of cutting-edge applications powered by Large Language Models (LLMs), contributing to code implementation, performance optimization, and debugging. • Requirement Translation & Feature Implementation: Collaborate closely with senior developers and product teams to deeply understand user requirements and translate them into high-quality functional modules. • LLM Models & Framework: Responsible for the design, development, and maintenance of LLM models within the team's proprietary LLM framework. • Advanced LLM Interaction: Skillfully apply prompt engineering techniques, context management, and advanced model interaction as part of LLM application development. • Continuous Learning & Growth: Actively learn and stay updated with the latest developments in LLM technologies, algorithms, and programming best practices. • Collaboration & Skill Enhancement: Actively participate in code reviews, pair programming sessions, and technical discussions to continuously grow your development skills. • Technical Problem Solving: Under the guidance of senior engineers, participate in technical problem-solving, performance optimization, and system debugging. • AI Agent System Productionization: Work closely with product and research teams to translate AI agent logic (e.g., tool-use, planning, reasoning) into robust, production-grade systems.