Senior Solution Engineer, Mission Control

Posted 4 Days Ago
Be an Early Applicant
3 Locations
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
NVIDIA seeks a Senior Solution Engineer for customer support and issue resolution in AI environments. Responsibilities include triaging software issues, documenting interactions, and collaborating with engineering teams on optimizing software performance.
Summary Generated by Built In

NVIDIA is looking for an engineer who wants the buzz of direct customer interaction, and the reward of contributing to software and products. We want the right person to join our team of Solution Engineers working on the NVIDIA Mission Control, which automates the operations of AI Factories.  We need an expert engineer to triage customer software issues and resolve customer problems. You must have excellent problem-solving abilities and communication experience and be able to work on multiple projects and tasks. You must be strong in Linux, have solid programming skills, and possess experience working with containers and related technologies such as Kubernetes.  Experience analyzing the distributed GPU-accelerated workload performance is a plus.

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++

The base salary range is 136,000 USD - 264,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

Ceph
Cuda
Docker
Gpfs
Kubernetes
Linux
Lustre
Python
PyTorch
Spark
TensorFlow
Wekaio
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The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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