Tech Stack
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.
AI
Communication @ 7
Debugging @ 6
Deep Learning
ElasticSearch @ 4
GPU
Grafana @ 4
HPC @ 4
JavaScript @ 7
Linux @ 4
Machine Learning @ 4
Mathematics @ 4
Observability @ 4
PyTorch @ 4
Python @ 7
Splunk @ 4
TensorFlow @ 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 has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, NVIDIA is using the potential of AI to define the next era of computing, with GPUs powering computers, robots, and self-driving cars.
Join a team that analyzes large-scale datacenter workloads on GPU-accelerated clusters. You will turn telemetry and workload data into clear findings and visuals, partnering with OS, container, GPU, and systems engineers. When useful, you will apply machine learning and deep learning techniques for categorization and forecasting, coordinating these efforts into tools the team uses.
Responsibilities
- Analyze large-scale workloads and infrastructure signals to identify application and platform improvement opportunities.
- Work with high-dimensional data to spot trends, connect changes to known events, summarize conclusions, and communicate results to engineers and leadership.
- Partner with the team to clarify questions, scope analyses, and document methods so others can extend your work.
- Build and maintain practical visualizations and lightweight implementations, such as machine learning and deep learning solutions for classification and prediction, within existing software workflows.
Requirements
- 5+ years of experience analyzing complex datasets, debugging data issues, and clearly communicating trends.
- BS or MS in Engineering, Mathematics, Physics, Computer Science, or equivalent experience.
- Strong Python and JavaScript skills.
- Ability to take responsibility for an analysis end to end.
- Hands-on experience with telemetry and observability stacks, such as Grafana, Elasticsearch, or Splunk.
- Understanding of core machine learning concepts.
- Strong analytical, problem-solving, collaboration, and communication skills.
Preferred Qualifications
- Experience with TensorFlow or PyTorch.
- Experience with Linux and HPC, large-scale, or performance-sensitive environments.
- Experience visualizing high-dimensional problems.
- A diligent, action-oriented analysis style.
Benefits
NVIDIA offers health care coverage, dental and vision coverage, 401(k) plans with company matching and after-tax contributions, an Employee Stock Purchase Program, an Employee Assistance Program, company-paid holidays, paid sick leave, vacation leave, professional time off, and life and disability protection. Employees are also eligible for equity and additional benefits.
The base salary range is USD 152,000–241,500. The final base salary is determined by location, experience, and the pay of employees in similar positions.