Nvidia Senior Solution Engineer AI Enterprise 

United States, Texas 

363776605

What you'll be doing

• Directly support NVIDIA’s Enterprise customers and work to answer questions, reproduce, resolve, or advance customer issues.

• Collaborate with multiple engineering teams on customer issues to drive root-cause analysis and deliver real solutions to customers.

• Contribute to product and support improvements through code, debugging, design feedback, or tools that accelerate issue resolution.

• Own and drive customer issues from inception to resolution.

• Document customer interactions to enrich our knowledge base and improve support effectiveness.

• Mentor early-career engineers on their journey to become successful Solution Engineers

• Define new standard methodologies, streamline cross-team collaboration, and take ownership of leading both projects and people.

• Occasional work on weekends and holidays to support customers

What we need to see

• Minimum of a BS in Computer Science, Electrical Engineering, or equivalent experience.

• At least 8 years of engineering experience with a proven track record in AI/ML-focused projects or enterprise-grade solutions, including at least 5 years leading engineering teams

• Deep understanding of Linux and the ability to analyze, optimize, and customize Linux environments for AI/ML workloads.

• Strong expertise in AI/ML training and inference, with experience deploying models at scale and applying them to real-world use cases such as chatbots, RAG pipelines, and vector search.

• Experience with common deep learning frameworks such as PyTorch or TensorFlow

• Exceptional communication skills with the ability to tailor technical depth to any audience, and remain calm and focused under pressure.

• Exceptionally organized and execution-focused, with a strong sense of follow-through and a genuine passion for solving complex problems.

• Proficient in Python and C/C++ programming, with experience contributing to large existing projects as well as building new tooling

• Experience building and deploying containerized solutions using Docker, Kubernetes, or Slurm.

Ways to stand out from the crowd

• Background with parallel programming or GPU acceleration (e.g., CUDA)

• Experience developing in GPU accelerated / cloud / virtualized environments

• Experience analyzing software performance of distributed workloads

• Clustering or HPC data center technologies including Upper Layer Protocols (NCCL, MPI)