Compiler Engineer - Backend

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4 Locations
In-Office or Remote
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re 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, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

We are looking for outstanding AI/ML compiler engineers to join the team and develop groundbreaking technologies in machine learning compilers and AI systems. We build innovative AI compiler solutions that works together with NVIDIA's software stack to provide comprehensive acceleration for modern machine learning models. As a member of the team, you will develop innovative AI compiler technologies for NVIDIA's hardware architecture. You will develop new ML/DL compiler abstractions, build runtimes, and ML/DL -compiler driven system solutions to accelerate large language models, agents and other high-impact machine learning workloads. As part of this role, you will be building a close technical relationship with internal NVIDIA software and hardware teams on push the latest developments to NVIDIA's product.

What you'll be doing:

  • Innovate and develop new machine learning compiler and systems technologies

  • Design, implement, and optimize compilers for high impact AI workloads

  • Co-design learning system solutions with current and future ML compiler and algorithm technologies.

  • Collaborate closely with other engineering teams at NVIDIA to build high impact solutions for machine learning acceleration

What we need to see:

  • Bachelor's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD are preferred

  • 5+ years (academic/ industry) experience with ML/DL systems development preferable for compilers

  • Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX etc.)

  • Strong python and C/C++ programming skills

Ways To Stand Out From The Crowd:

  • Expertise in AI frameworks such as PyTorch, Jax and ONNX

  • Expertise in machine compilers (e.g. Apache TVM, MLIR)

  • Strong experience in GPU performance optimizations

  • Strong experience machine learning systems research and productionization

  • Open source project ownership or contributions

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 - 287,500 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.

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The Company
HQ: Santa Clara, CA
21,960 Employees
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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