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NVIDIA

Designs the chips and software that power AI

Principal Software Engineer - Employee Productivity

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, another Engineering field, or a related field, or equivalent experience.
  • At least 15 years of full-stack product engineering experience, including at least 3 years at the principal or staff level guiding cross-functional teams.
  • A proven track record delivering consumer-grade web and/or mobile experiences at scale.
  • Expertise in search, recommendation, or applied-AI systems.
  • Hands-on experience with modern cloud infrastructure, Kubernetes, and automated continuous integration and continuous delivery.
  • Strong data modeling skills with relational and NoSQL stores.
  • Fluency in application security.
  • Excellent mentoring skills and comfort setting vision while contributing hands-on.

Responsibilities

  • Lead and code end-to-end features for an AI-rich employee experience across web and native mobile apps.
  • Architect highly performant services and user interfaces that surface personalized content, knowledge, and search results to a global workforce.
  • Embed large language model and vector-search capabilities into existing product surfaces, driving relevance and continuous learning loops.
  • Own system design reviews, code reviews, and technical roadmaps; raise the engineering bar and mentor engineers across the team.
  • Integrate third-party human resources information systems, collaboration, and productivity platforms to create cohesive, automated user journeys.
  • Champion modern front-end patterns, including React, Next.js, TypeScript, and Tailwind, and cloud-native back-end practices, including Kubernetes, containers, and continuous integration and continuous delivery.
  • Instrument observability, tracing, structured logging, and service-level agreement dashboards to help site reliability engineers achieve 24×7 reliability for employees in every region.
  • Uphold security, privacy, and accessibility standards across all user journeys.

Desired Qualifications

  • Shipped generative AI features, such as retrieval-augmented generation, copilots, or chatbots, to thousands of daily users.
  • Contributions to open-source search or front-end frameworks.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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