NVIDIA is hiring for the position of Systems Data Engineer. This is a full-time opportunity open to both remote and on-site candidates (Santa Clara, CA), ideal for professionals experienced in data analytics, machine learning, and performance optimization. Join a team working on cutting-edge GPU and AI technologies that power large-scale data center infrastructures. All essential job details, skills required, and application links are shared below.
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- Company: NVIDIA
- Title: Systems Data Engineer
- Location: Santa Clara, CA / Remote (USA)
- Job Type: Full-Time
- Job Requisition ID: JR1999730
- Salary: Up to $200k/ yr (Expected)
About the Role
As a Systems Data Engineer at NVIDIA, you’ll analyze high-dimensional workloads in large-scale GPU datacenters to identify performance and infrastructure optimization opportunities. You’ll work alongside experts in deep learning, container technologies, and HPC environments to help design and refine scalable systems for AI workloads.
Key Responsibilities
- Analyze large-scale workloads and identify infrastructure improvements
- Build visualizations and insights for performance tuning and architecture decisions
- Apply ML techniques for classification and predictive insights
- Integrate solutions into existing software toolsets
- Collaborate with cross-functional teams across software, systems, and AI research
Basic Qualifications
- 4+ years of experience in data analysis, debugging, and visualization
- Bachelor’s or Master’s in Engineering, CS, Math, or Physics
- Proficient in Python and JavaScript
- Exposure to tools like Grafana, Splunk, or ElasticSearch
- Understanding of machine learning fundamentals
Preferred Qualifications
- Experience with deep learning frameworks (TensorFlow, PyTorch)
- Background in large-scale computing or high-performance clusters
- Strong visualization skills for complex data problems
- Familiarity with Linux and open-source data tools
Why Join NVIDIA?
- Be at the forefront of AI and GPU computing innovation
- Work with a globally respected team solving high-impact problems
- Flexible remote or on-site work with great benefits
