Senior Full-Stack Software Engineer - VLSI Tools

NVIDIA•Durham, NC
•$152,000 - $287,500

About The Position

NVIDIA is seeking a highly motivated Full-Stack Web Applications Engineer for its Hardware Infrastructure team. The team builds scalable web services for VLSI designs and develops and maintains services intended to improve chip-design productivity. The position is part of a multifaceted Agile software team with high production-quality standards. The engineer will work on backend and frontend web applications for VLSI design and modeling, support a large-scale data platform, and build infrastructure and microservices for big-data use cases.

Requirements

  • At least 5 years of experience.
  • Bachelor’s or master’s degree in Computer Science or a related engineering field, or equivalent experience.
  • Knowledge of VLSI design, modeling, and verification.
  • Experience with JavaScript and Node.js.
  • Knowledge of modern frontend frameworks such as Vue.js, React.js, Svelte, or Ember.js.
  • Comprehensive understanding of web development core concepts and industry standards.
  • Experience designing and developing distributed microservices.
  • In-depth understanding of database concepts and object modeling.
  • Detailed knowledge of object-oriented design, data structures, and algorithms.
  • Excellent interpersonal skills.

Nice To Haves

  • In-depth familiarity with coding assistant tools such as Cursor, Claude Code, or Co-pilot.
  • Background with SQL and at least one SQL database server.
  • Experience developing web services for chip design, modeling, and verification.
  • Experience with MongoDB or other NoSQL datastores and knowledge of Python or Golang.
  • Flexibility and adaptability when working in a dynamic, diverse environment with different frameworks and requirements.

Responsibilities

  • Design and develop the backend and frontend of web applications for VLSI design and modeling.
  • Collect requirements and consult with end users about their needs and use cases.
  • Analyze performance bottlenecks.
  • Support and maintain a large-scale data platform with high QoS.
  • Build infrastructure and microservices for various big-data scenarios.

Benefits

  • Eligible for equity and benefits.
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