Senior Deep Learning Tools Engineer – CUDA Tile

NVIDIA; Salt Lake City (UT); On-site; USD 152,000 - 241,500; Full time

Benefits offered by this job

Equity

Comprehensive benefits package

Job summary

NVIDIA is seeking a Deep Learning Compiler & Tools Engineer in Salt Lake City, Utah, to join their advanced compiler technologies team. You will focus on performance validation and analysis, collaborating closely with compiler developers and hardware teams. The role requires strong programming skills, experience in performance engineering, and familiarity with deep learning frameworks. You can expect a competitive salary range of $152,000 - $241,500, equity, and an attractive benefits package.

Qualifications

• 5+ years of software engineering experience, including performance engineering and optimization.
• Strong programming skills in Python; C++ is a plus.
• Familiarity with deep learning frameworks like PyTorch or TensorFlow.

Responsibilities

• Design and develop performance testing frameworks for deep learning compilers.
• Implement benchmarking systems to measure performance of AI workloads.
• Analyze performance trends and identify optimization opportunities.

Skills

Performance engineering

Benchmarking

Python programming

CI/CD automation

Deep learning frameworks

Data analysis

Education

BS, MS, or PhD in Computer Science or related field

Tools

CI/CD systems

GPU systems

Job description

NVIDIA is building advanced compiler technologies to accelerate AI workloads, and we are looking for an engineer focused on performance validation, analysis, and tracking. In this role, you will work at the intersection of deep learning compilers, GPU systems, and automation infrastructure, ensuring that performance improvements are measurable, scalable, and continuously validated over time.

Do you want to help drive the performance of next‑generation compilers? Are you excited by how GPU performance powers breakthroughs in deep learning, autonomous systems, and high‑performance computing? We are seeking a talented Deep Learning Compiler & Tools Engineer focused on CUDA Tile (Performance & Infrastructure) to join our team.

You will collaborate closely with compiler developers, infrastructure providers, and hardware teams to build systems that track, analyze, and improve performance across rapidly evolving AI workloads. If you’re passionate about performance, systems, and building infrastructure that drives real‑world impact, we want to hear from you.

What You’ll Be Doing

• Design and develop performance testing frameworks for deep learning compilers and workloads
• Build and maintain automated pipelines (CI/CD) to continuously track performance across models, hardware, and compiler changes
• Implement benchmarking systems to measure latency, throughput, and efficiency of AI and HPC workloads
• Analyze performance trends over time and identify regressions, bottlenecks, and optimization opportunities
• Partner with compiler and architecture teams to debug and resolve performance issues
• Develop tools and dashboards for performance visualization, reporting, and insights
• Enable scalable testing across diverse GPU systems and environments
• Improve infrastructure to ensure reliable, reproducible, and high‑signal performance data

What We Need To See

• BS, MS, or PhD (or equivalent experience) in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or related field
• 5+ years of software engineering experience, including experience in performance engineering, benchmarking, or systems optimization
• Strong programming skills in Python (C++ is a plus)
• Experience with CI/CD systems and automation frameworks
• Familiarity with hardware‑aware performance analysis (GPUs, accelerators, or similar systems)
• Experience working with deep learning frameworks such as PyTorch, TensorFlow, JAX, or TensorRT
• Background in data analysis, profiling, and regression tracking
• Ability to debug complex system‑level issues across software and hardware layers

Ways to Stand Out from the Crowd

• Experience with GPU performance analysis and optimization
• Understanding of compiler internals (LLVM, MLIR, CUDA compilation flow)
• Experience building performance dashboards and large‑scale telemetry systems
• Familiarity with hardware/software co‑design or low‑level performance tuning
• Experience with distributed testing infrastructure or large‑scale benchmarking systems

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered one of the most desirable employers in the technology industry. Our teams are tackling some of the most challenging problems in AI, deep learning, and accelerated computing.

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.

Equal Opportunity Employer

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.