System Software Engineer, Distributed Systems

Posted 16 Hours Ago
Be an Early Applicant
Santa Clara, CA
Mid level
Artificial Intelligence • Hardware • Robotics • Software • Metaverse
The Role
The role involves designing, developing, and delivering core components of VLSI productivity platforms, translating high-level requirements into actionable tasks, building scalable systems, and modernizing legacy codebases. Collaboration with engineering teams to improve efficiency is key.
Summary Generated by Built In

We are looking for inquisitive and driven full-time software engineers with a strong interest in building high-quality, long-lasting systems.

The VLSI Productivity and Infrastructure team supports hundreds of chip design engineers by building tools and platforms that supercharge their everyday work. From databases to web applications and build automation to machine learning, our team handles it all. Want to know how NVIDIA stays at the top of the pack? Come join us to find out!

What you will be doing:

You will be responsible for design, development and delivery of core components of our next-generation VLSI productivity platforms.

  • Design, build, deploy and improve highly scalable systems

  • Translate high-level requirements into actionable tasks/deliverables

  • Jump between microservices and monoliths as needed to build efficient products

  • Convert legacy codebases into modern powerhouses infused with industry best-practices

  • Collaborate with engineering teams to identify and alleviate bottlenecks in their daily tasks

What we need to see:

  • B.S. EE/CS (or equivalent experience)

  • 3+ years developing large-scale software applications in an enterprise engineering environment using Typescript, Python and/or Golang

  • Full-stack experience building backend services with APIs, message queues, SQL and NoSQL databases, and frontend web apps in React or other popular frameworks

  • Solid computer science fundamentals in algorithms/data structures/complexity analyses

  • Excellent grasp of distributed systems and microservices

Ways to stand out from the crowd:

  • Experience building custom solutions around open-source products and libraries to solve feature-gaps fast

  • You've been your own DevOps engineer, equally comfortable deploying your services and infrastructure on a cloud provider and on bare-metal servers

  • Solid fundamentals of UNIX internals, filesystems, job-scheduling, processes, synchronization, and locks

  • Highly self-sufficient in the face of ambiguity, with strong reasoning and problem-solving skills

  • Deeply interested in learning disparate concepts and putting them together in innovative new ways

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse 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.

Top Skills

Go
Python
Typescript
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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