出海雷达

高级系统软件工程师,代理检索

Senior System Software Engineer, Agentic Retrieval

AI开发工程限定地区(需当地身份)
公司NVIDIA
薪资$184,000 - $356,500/年
工作地点Canada, United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间11 天前
数据来源Himalayas
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注意地域限制:该职位明确限定在 Canada、United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

NVIDIA 的技术是人工智能革命的核心,通过为自动驾驶汽车、机器人、副驾驶等提供动力,影响着全球人们的生活。加入我们,站在智能助手和信息检索技术发展的最前沿。NVIDIA 正在寻找一名系统软件工程师 - 代理检索,以开发用于索引和查询多模态内容的流程。我们希望找到一位对在生成式 AI、LLM、VLLM 和代理检索领域解决世界上最复杂的问题充满热情的人,利用我们的创新硬件和软件平台。你将开发用于构建由大型语言模型 (LLM) 驱动的强大、灵活的多模态检索器和代理工具,从而提升数百万客户的体验。如果你富有创造力,并热衷于解决现实世界的对话式 AI 问题,欢迎加入我们。

此职位在加速容器化流程以实现高质量多模态数据集方面至关重要,并提供一流的检索效果。日常工作的重点是开发高效、可扩展的系统,用于去重、过滤和分类训练语料库,以增强现成模型的能力。这些工作的核心是通过微优化、提示工程、微调和应用新研究,持续测试和改进系统成本、速度和准确性。理想的候选人相信工艺精神,他们早期发布并频繁获取反馈,同时保持长期愿景!他们能够客观评估最新的 AI 模型和框架,关注加速和能力提升。

你将负责:

  • 开发和优化基于 Rust 的数据处理框架,在 GPU 加速环境中高效处理大规模数据集,这对 LLM 训练至关重要。
  • 领导代理检索流程组件的开发和迭代优化,确保其展示 GPU 加速和最佳性能模型,以改善总拥有成本 (TCO)。
  • 与 LLM 和 ML 研究团队合作,开发全栈、GPU 加速的数据准备流程,用于多模态模型。在各种系统架构中实施基准测试、分析和优化创新算法,特别针对 LLM 应用。
  • 与多样化团队紧密合作,理解需求,构建和评估原型,并开发
查看英文原文

NVIDIA's technology is at the heart of the AI revolution, touching people across the planet by powering everything from self-driving cars, robotics, co-pilots and more. Join us at the forefront of technological advancement in intelligent assistants and information retrieval. NVIDIA is looking for a System Software Engineer - Agentic Retrieval to develop pipelines for indexing and querying multi-modal content. We are looking for someone with a passion for working with the world's most challenging problems in Generative AI, LLM, VLLM, and Agentic Retrieval spaces using our innovative hardware and software platforms. You will develop tools for building powerful, flexible, multi-modal retrievers and agents driven by Large Language Models(LLM) thereby improving the experience of millions of customers. If you're creative & passionate about solving real world conversational AI problems, come join us.

This role is pivotal in accelerating containerized pipelines for high quality multi-modal datasets and providing best-in-class retrieval efficacy. The day-to-day focus is on developing efficient, scalable systems for deduplicating, filtering, and classifying training corpora for tailored models that enhance off-the-shelf capabilities. Fundamental to these efforts are iterative testing and improvement in system cost, speed, & accuracy through micro-optimization, prompt engineering, fine tuning, and applying new research. The ideal candidate believes in craftsmanship whereby they release early and often to obtain feedback while keeping the long-term vision alive! They are comfortable objectively evaluating the latest AI models and frameworks with an eye towards acceleration and capability enhancement.

What You'll Be Doing:

  • Develop and optimize Rust-based data processing frameworks, ensuring efficient handling of large datasets on GPU-accelerated environments, vital for LLM training.
  • Lead development and iterative optimization of components for Agentic Retrieval pipelines, ensuring they demonstrate GPU acceleration & the best performing models for improved TCO.
  • Collaborate with teams of LLM & ML researchers in the development of full-stack, GPU-accelerated data preparation pipelines for multimodal models Implement benchmarking, profiling, and optimization of innovative algorithms in Python in various system architectures, specifically targeting LLM applications.
  • Work closely with diverse teams to understand requirements, build & evaluate POCs, and develop roadmaps for production level tools and library features within the growing LLM ecosystem.
  • Build amazing products to improve employee productivity using Gen-AI & Co-pilot experiences!
  • Develop integrated systems enabling unified experience across applications and driving insights for end-to-end user experience.
  • Help build and maintain our Continuous Delivery pipeline with the goal of moving changes to production faster and safer, while ensuring key operational standards.
  • Provide peer reviews to other specialists including feedback on performance, scalability, and correctness and actively contribute to the adoption of frameworks, standards, and new technologies

What We Need To See:

  • Bachelor’s or Master’s Degree program in Computer Science, Computer Engineering, or a related field (or equivalent experience).
  • 6+ years of experience in a similar or related role
  • Experience delivering software in a cloud context and is familiar with the patterns and process of managing cloud infrastructure
  • Knowledge of MLOps technologies such as Docker-Compose, Containers, Kubernetes, data center deployments etc
  • Excellent in-depth hands-on understanding of NLP, LLM, VLM, Generative AI, and Agentic Retrieval workflows
  • Self-starter with a passion for growth, enthusiasm for continuous learning and sharing findings across the team
  • Outstanding communication skills for distilling sophisticated topics down to understandable, impactful conclusions..
  • Ability to work successfully with multi-functional teams, principals, and architects. Coordinates optimally across organizational boundaries and geographies.

If you are passionate about technology, have a proven track record in system software engineering, and are eager to make a significant impact in the industry, we would love to hear from you. Join us at NVIDIA and help us craft the future of visual computing!
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 October 6, 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.Originally posted on Himalayas

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