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Senior Solution Engineer, AI Enterprise

NVIDIA

New York, NYOn Site

Original Job Summary

Overview

NVIDIA is looking for an engineer who thrives at the intersection of innovative technology and real-world customer applications. As a Senior Solution Engineer, AI Enterprise, you will support the NVIDIA AI Enterprise product line, working directly with customers to address datacenter-scale AI/ML workloads, resolve issues, and contribute to evolving products and support software.

Key Responsibilities

  • Support NVIDIA Enterprise customers by addressing technical issues.
  • Collaborate with cross-functional engineering teams for root-cause analysis.
  • Contribute to product improvements through coding, debugging, and design feedback.
  • Own and drive customer issues from inception to resolution.
  • Document customer interactions to build a robust knowledge base.
  • Mentor early-career engineers and lead strategic projects.
  • Occasional weekend and holiday support for customers.

Qualifications

  • BS in Computer Science, Electrical Engineering, or equivalent.
  • 8+ years engineering experience with 5+ years in leadership.
  • Expertise in AI/ML training, inference, and real-world deployments.
  • Deep understanding of Linux environments and optimization for AI/ML.
  • Proficiency in Python and C/C++, with experience in containerized solutions.
  • Experience with Docker, Kubernetes, and Slurm.
  • Strong communication skills tailored to varied audiences.

Preferred Skills

  • GPU acceleration and parallel programming (e.g., CUDA).
  • Experience with cloud and virtualized environments.
  • Familiarity with distributed workloads and HPC technologies.

Compensation & Benefits

Competitive base salary, equity, and benefits. Base salary ranges are provided based on level with applications accepted until August 8, 2025.

Key skills/competency

  • AI
  • ML
  • Linux
  • Python
  • C/C++
  • Containerization
  • GPU
  • Debugging
  • Mentoring
  • Enterprise

How to Get Hired at NVIDIA

🎯 Tips for Getting Hired

  • Customize resume: Highlight AI/ML and leadership experiences.
  • Demonstrate expertise: Emphasize Linux, Python, and containerization.
  • Research NVIDIA: Understand their products and engineering culture.
  • Prepare examples: Showcase complex problem-solving and project leadership.

📝 Interview Preparation Advice

Technical Preparation

Review AI/ML frameworks and Linux optimization.
Practice Python and C/C++ coding challenges.
Study container orchestration with Docker and Kubernetes.
Research GPU acceleration techniques and CUDA basics.

Behavioral Questions

Describe a challenging project you led.
Explain handling high-pressure customer situations.
Discuss mentoring experiences with junior engineers.
Outline strategies for cross-team collaboration.