- 4+ years of Solutions Engineering (or similar Sales Engineering roles)
- 3+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience extremely helpful.
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience.
- Established track record of deploying solutions in cloud computing environments including AWS, GCP, or Azure
- Knowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, data center deployments
- Ability to use at least one scripting language (i.e., Python)
- Good programming and debugging skills
- Ability to communicate your ideas/code clearly through documents, presentation etc.
Ways to stand out from the crowd
- AWS, GCP or Azure Professional Solution Architect Certification.
- Hands-on experience with NVIDIA GPUs and SDKs (e.g. CUDA, RAPIDS, Triton etc.)
- System-level experience specifically GPU-based systems
- Experience with Deep Learning at scale
- Familiarity with parallel programming and distributed computing platforms
We make extensive use of conferencing tools, but occasional travel is required for local on-site visit to customers and industry events. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.