Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Software Development @ 7
Python @ 7
GPU @ 4
AI @ 4
Profiling @ 4
Performance Analysis @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA GPU Architecture Group is seeking a senior software engineer to automate and optimize performance analysis workflows for AI training and inference workloads. You will perform analysis and build scalable tools and workflows used across a broad audience of engineers to push AI workload optimization boundaries.
Responsibilities
- Design and build performance analysis tools and workflows for AI training and inference workloads.
- Understand how AI performance engineers work and translate their needs into scalable, intuitive tooling.
- Develop integrations between profiling infrastructure and AI frameworks and workflows.
- Collaborate with performance engineers, hardware architects, and software teams to ensure profiling capabilities align with real-world AI workloads.
- Identify performance bottlenecks in AI workloads and develop automated approaches to detect and diagnose them.
Requirements
- M.S. or PhD in Computer Science, Computer Engineering, or a related field (or equivalent experience).
- 6+ years of relevant work experience.
- Deep knowledge of AI workloads, frameworks, and performance characteristics.
- Experience building tools, workflows, or infrastructure used by other engineers.
- Strong software development skills (Python, C++ preferred).
- Ability to translate user requirements into scalable tooling solutions.
- Up to date with AI-enabled tooling for software development and performance analysis.
- Strong interpersonal skills for understanding engineer difficulties and working across multi-functional teams.
Ways to stand out
- Experience profiling or optimizing AI training or inference pipelines at scale.
- Background building developer tools or platforms for ML engineers.
- Contributions to open-source AI tooling or frameworks.
Compensation and benefits
- Base salary ranges (location, experience, and level dependent):
- Level 4: 168,000 USD - 270,250 USD
- Level 5: 200,000 USD - 322,000 USD
- Eligible for equity and benefits.
Additional information
- Applications for this job will be accepted at least until May 19, 2026.
- This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.