Nvidia Senior Solution Engineer Mission Control 

United States, Texas 

81905737

What you'll be doing:

• Provide direct support to our NVIDIA Enterprise customers and work to answer questions, reproduce, or resolve customer issues.

• Work with engineering teams on customer issues, providing logs, reproduction information, and other triage information.

• Create/update product and/or support tools.

• Own and drive customer issues from inception to resolution.

• Document customer interactions and better enhance our knowledge base.

• Work with the latest hardware (e.g. GPUs, AI accelerators, high-speed interconnects) and software technologies such as parallel filesystems (e.g. Lustre, GPFS, WekaIO), Jupyter, and various ML frameworks and tools, Spark, Kubernetes, and Ceph

• 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 5+ years of engineering experience with a proven track record in AI/ML-focused projects or enterprise-grade solutions.

• Expertise analyzing, optimizing, and customizing Linux environments for AI/ML workloads.

• Strong container orchestration/job scheduling experience on compute clusters, especially with Kubernetes

• Professional-level communication experience, able to adjust to the technical level of the audience, and stay calm and focused in negative situations.

• Excellent follow-up and organizational skills, with a love for solving problems.

• Proficient in Python programming with the ability to develop scripts and build custom tools. Experience with parallel programming or GPU acceleration (e.g., CUDA) is highly desirable.
  

Ways to stand out from the crowd:

• Experience with Chatbots, RAG pipelines, vector databases, distributed training or inference workloads

• Experience developing in GPU accelerated / cloud / virtualized environments

• Containerized solutions/job scheduling experience with knowledge of Docker and/or Kubernetes and/or Slurm, and/or experience analyzing software performance of distributed workloads

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

• Experience developing with C/C++