Senior Deep Learning Compiler Engineer
NVIDIA · Austin, TX
- On site
- Full-time
- $241,500 / year
- Austin, TX
Tailored resume — keyword-matched to this role.
Hiring manager — we find who's hiring.
Intro email — drafted to reach them directly.
Job highlights
- Develop compiler optimizations for deep learning networks.
- Collaborate with framework and hardware teams.
- Define APIs and performance optimizations.
- Requires strong C/C++ and Python skills.
- Experience with compiler technologies is key.
About the role
About NVIDIA
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.About the Role
We are looking for a Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AIs, recommendation systems, image classification, speech recognition, etc. Our DLC has been the backbone of NVIDIA inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Tine and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community.What You'll Be Doing
- Analyzing deep learning networks and developing compiler optimization algorithms.
- Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software.
- Defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work.
What We Need To See
- Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience.
- 3+ years of relevant work or research experience in performance analysis and compiler optimizations.
- Ability to work independently, define project goals and scope, and lead your own development efforts.
- Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design.
- Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team.
Ways To Stand Out From The Crowd
- Proficient in CPU and/or GPU architecture.
- CUDA or OpenCL programming experience.
- Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation.
- Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch.
- GPU kernel generation with high performance and fast build time.
- A track record of success in mentoring junior engineers and interns is a bonus.
Compensation and Benefits
With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits.Key skills/competency
- Deep Learning Compiler Engineer
- Compiler Optimization
- Performance Analysis
- GPU Architecture
- CUDA
- MLIR
- LLVM
- Deep Learning Frameworks
- PyTorch
- C++
Skills & topics
- Deep Learning
- Compiler Engineer
- NVIDIA
- AI
- Machine Learning
- GPU
- Software Engineer
- Computer Science
- Performance Optimization
- C++
- Python
- MLIR
- LLVM
- CUDA
How to get hired
- Tailor your resume: Highlight experience in performance analysis, compiler optimizations, and C/C++/Python skills, emphasizing any work with deep learning frameworks and GPU architecture.
- Showcase relevant projects: Detail personal projects or research involving MLIR, LLVM, CUDA, or other compiler technologies, and be ready to discuss them.
- Prepare for technical interviews: Expect questions on algorithms, data structures, compiler design, deep learning concepts, and GPU programming. Practice coding challenges.
- Demonstrate problem-solving: Be ready to discuss how you approach complex technical challenges, define project scope, and work independently.
Technical preparation
Master C++ and Python for compiler development.,Study GPU architecture and CUDA programming.,Practice with MLIR, LLVM, and deep learning frameworks.,Develop algorithms for compiler optimization.
Behavioral questions
Describe a challenging compiler optimization problem.,How do you collaborate with hardware teams?,How do you define project goals and scope?,Share an experience mentoring junior engineers.
Frequently asked questions
- What is the expected salary range for a Senior Deep Learning Compiler Engineer at NVIDIA?
- The base salary range for this role at NVIDIA is between $152,000 and $241,500 USD annually. This is complemented by eligibility for equity and other benefits, with the final determination based on location, experience, and internal pay equity.
- What specific programming languages are essential for the Senior Deep Learning Compiler Engineer role at NVIDIA?
- Excellent C/C++ and Python programming and software design skills are essential for this role. Proficiency in debugging, performance analysis, and test design using these languages is required.
- What deep learning frameworks or technologies are most relevant for this position?
- Experience with deep learning frameworks such as PyTorch is highly valued. Familiarity with technologies like MLIR, XLA, TVM, and LLVM is also a significant advantage for this Deep Learning Compiler Engineer role.
- Does NVIDIA offer remote work options for the Senior Deep Learning Compiler Engineer position?
- The job description does not explicitly state the work arrangement. However, NVIDIA has a diverse work environment and often offers hybrid or remote options for engineering roles. It's best to clarify during the application or interview process.
- What kind of compiler experience is NVIDIA looking for in a Deep Learning Compiler Engineer?
- NVIDIA seeks experience in compiler optimizations, performance analysis, and implementing compiler infrastructure techniques for neural networks. Proficiency with technologies like MLIR, XLA, TVM, and LLVM is particularly sought after for this Deep Learning Compiler Engineer role.
- Is a Ph.D. required for the Senior Deep Learning Compiler Engineer position at NVIDIA?
- A Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, a related field, or equivalent experience is acceptable. While a Ph.D. can be beneficial, extensive relevant work or research experience is also highly valued.
- What are the key responsibilities of a Deep Learning Compiler Engineer at NVIDIA?
- Key responsibilities include analyzing deep learning networks, developing compiler optimization algorithms, collaborating with deep learning software framework and hardware architecture teams, defining public APIs, and ensuring high performance and fast build times for GPU kernel generation.