NVIDIA

NVIDIA

Posted via Workday

Senior Software Engineer, Deep Learning - MLIR TRT

Posted Aug 5, 2026

Role at a glance

Salary
$184K – $356.5K/yr
Location
Santa Clara, California, United States
Work arrangement
On-site
Employment
Full-time
Education
MS or PhD degree in computer science, computer vision, robotics, computer architecture or equivalent experience in technical field

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Role Summary

AI-generated

This role develops and productizes deep learning solutions for autonomous driving vehicles within NVIDIA’s Solution Engineering-Automotive Machine Learning team. The work focuses on compiler technology and software workflows that optimize deep learning models for NVIDIA hardware and support Physical AI systems and customer workloads.

What You'll Do

  • Develop compiler technologies to accelerate deep learning inference on NVIDIA hardware platforms for Physical AI
  • Work across model fine-tuning, quantization, low-level kernel development, and performance optimization
  • Develop workflows using frameworks such as PyTorch and JAX and compiler tools such as MLIR and Triton
  • Work with customers to accelerate their workloads on NVIDIA platforms
  • Implement and experiment with new deep learning research insights to improve NVIDIA’s Physical AI DNNs
  • Coordinate with architecture and software teams to develop solutions for partners working on NVIDIA platforms

Generated from the employer's posting. Verify important details before applying.

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Qualifications

MS or PhD degree in computer science, computer vision, robotics, computer architecture or equivalent experience in technical field; 5+ years of software development experience; 2+ years developing deep learning frameworks or compiler technologies; GPU programming or system-level optimization experience; strong C/C++ programming skills; familiarity with deep learning techniques for inference and training; strong analytical skills.

Required

  • MS or PhD degree in computer science, computer vision, robotics, computer architecture or equivalent experience in technical field
  • 5+ years of work experience in software development
  • 2+ years of experience developing deep learning frameworks such as PyTorch, JAX, TensorFlow, or ONNX, or compiler technologies such as...
  • Experience with GPU programming technologies such as CUDA C++ or DSLs like OpenAI Triton, or system-level optimization for deep learning...
  • Strong C/C++ programming skills
  • Familiarity with state-of-the-art deep learning techniques for inference and training
  • Strong analytical skills

Preferred

  • Experience with MLIR, LLVM, or similar compiler technologies
  • Background with low precision inference, quantization, or compression of DNNs
  • Experience with GPU programming
  • Experience building DSLs or optimizing compilers for GPUs or other accelerated computing platforms
  • Open source project ownership or contribution, healthy GitHub repositories, guiding and/or mentoring experience

Original job description

Content provided by the employer

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 Senior Deep Learning Software Engineers to develop and productize NVIDIA's deep learning solutions in autonomous driving vehicles. In the Solution Engineering-Automotive Machine Learning team, we are developing new technologies to allow more capable deep learning models to be deployed in Physical AI systems. As part of the role, you will develop compiler technology to allow larger and better models to be optimized to leverage NVIDIA’s unique hardware architecture. You will also be exposed to the most pressing problems that our partners face during product development and coordinate with other architecture and software teams to develop the best solution for partners working on our platforms.

What you'll be doing:

  • Developing compiler technologies to accelerate deep learning inference on NVIDIA hardware platforms for Physical AI.

  • Working across a wide range of abstractions from model fine-tuning and quantization to low-level kernel development and performance optimization.

  • Develop workflows that let users leverage frameworks (e.g. PyTorch, JAX) and compiler technologies tools (e.g. MLIR, Triton) without forgoing performance

  • Work with customers to help accelerate their workloads on NVIDIA platforms.

  • Stay up to date with the latest research and innovations in deep learning, implement and experiment with new insights to improve NVIDIA's Physical AI DNNs.

What we need to see:

  • MS or PhD degree in computer science, computer vision, robotics, computer architecture or equivalent experience in technical field (or equivalent experience)

  • 5+ years of work experience in software development.

  • 2+ years of experience in **developing** deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc.) or compiler technologies (e.g. LLVM, MLIR, TVM, Triton, etc.).

  • Domain experience in technologies used for GPU programming (e.g. CUDA C++ and/or DSLs like OpenAI Triton) or with system-level optimization for deep learning training or inference.

  • Strong C/C++ programming skills

  • Familiar with start-of-the-art deep learning techniques for inference and training.

  • Willing to take action and have strong analytical skills.

Ways to stand out from the crowd:

  • Experience with MLIR or LLVM or similar compiler technologies

  • Background with low precision inference, quantization, compression of DNNs

  • Experience with GPU programming

  • Experience with building DSLs or optimizing compilers (e.g. graph compiler or kernel generator) for GPUs or other accelerated computing platforms.

  • Open source project ownership or contribution, healthy GitHub repositories, guiding and/or mentoring experience

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

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 January 13, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

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.

NVIDIA

About the company

NVIDIA

Large Enterprise

NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.