Senior Software Engineer, At Scale Compute Analysis

NVIDIA•Santa Clara, WA

3d•$152,000 - $241,500

About The Position

Join a team that analyzes large-scale datacenter workloads on GPU-accelerated clusters. The role turns telemetry and workload data into clear findings and visualizations, partnering with OS, container, GPU, and systems engineers. When useful, machine learning and deep learning techniques are applied for categorization and forecasting and coordinated into tools the team uses. The position analyzes large-scale workloads and infrastructure signals to identify application and platform improvement opportunities. It involves working with high-dimensional data, finding trends, connecting changes to known events, summarizing conclusions, and communicating results to engineers and leadership. The engineer will clarify questions and scope analyses with the team, document methods so others can extend the work, and build and maintain practical visualizations and lightweight implementations within existing software workflows.

Requirements

At least 5 years of experience analyzing complex datasets, debugging data issues, and communicating trends clearly.
BS or MS in Engineering, Mathematics, Physics, or Computer Science, or equivalent experience.
Strong Python and JavaScript skills.
Comfort taking responsibility for an analysis end-to-end.
Hands-on use of telemetry or observability stacks such as Grafana, Elasticsearch, or Splunk.
Demonstrated grasp of core machine learning concepts.
Quick learning ability and strong analytical and problem-solving skills.
Collaboration and communication skills.

Nice To Haves

Experience with TensorFlow or PyTorch.
Linux experience and experience in HPC, large-scale, or performance-sensitive environments.
Experience visualizing high-dimensional problems.
A diligent, action-biased analysis style.

Responsibilities

Analyze large-scale workloads and infrastructure signals to find application and platform improvement opportunities.
Analyze high-dimensional data to spot trends, connect changes to known events, summarize conclusions, and communicate results to engineers and leadership.
Work with the team to clarify questions and scope analyses.
Document analysis methods so others can extend the work.
Build and maintain practical visualizations and lightweight implementations, including ML/DL for classification or prediction, within existing software workflows.