Nvidia Software Engineer Benchmarking Analysis 

Israel, North District 

595069151

We are looking for an experienced Software Engineer to take part in the design and development of next-generation performance engineering frameworks. In this role, you will focus on Python-based benchmarking and analysis systems, while also contributing to high-performance components in C/C++. You’ll work on challenges at the intersection of networking, distributed computing, and AI, building tools that run at scale on clusters, clouds, and data centers.

What you'll be doing:

• Design and implement performance benchmarking and analysis frameworks for next-generation AI and HPC workloads

• Work across Python (primary) and C/C++ (for performance-critical modules) to deliver reliable and scalable tools

• Take full technical ownership of our core telemetry engine, including utilizing Jupyter Notebooks and other data analysis frameworks to help performance engineers analyze telemetry results.

• Contribute to our DevOps environment, owning the CI/CD pipelines and release processes for your projects

• Drive technical innovation in the performance engineering ecosystem, including taking part in building our next-gen agentic AI assistant

What we need to see:

• B.Sc. in Computer Science, or a related engineering field

• 3+ years of professional software development experience

• A proven track record of technical ownership, driving a technical agenda, and problem solving

• High-level Python development skills, building robust, well-structured, production-grade applications

• C/C++ experience, especially for performance-critical or low-level components

• Experience with modern CI/CD pipelines and DevOps practices

Ways to stand out from the crowd:

• Linux systems knowledge, including software packaging (RPM, DEB), and an understanding of the complexities of software distribution and dependencies

• Experience with the Python data analysis and visualization frameworks (e.g., h5py, pandas, NumPy, Matplotlib/Plotly)

• Experience with Slurm, Kubernetes, MPI, or other distributed job orchestration and cluster management systems

• Familiarity with agentic AI concepts or frameworks (e.g., RAG techniques, LangChain, LangGraph, LlamaIndex, etc.)

• Experience contributing to open-source projects