Join the Solutions Architect team at NVIDIA’s AI Software Segment SA, where you will leverage your expertise in deep learning, Generative AI, and Cloud technologies to develop end-to-end AI solutions for enterprise customers. Your day-to-day involves tackling sophisticated challenges across the AI model lifecycle, from data processing and training to reinforcement learning and optimization, while supporting a broad portfolio of models including LLMs and multimodal applications. You will collaborate closely with customers to customize AI workloads at scale, co-designing solutions that address their unique needs and contribute to NVIDIA’s product development by sharing your knowledge through open-source projects and hands-on training. Ideal candidates have 5+ years of experience with AI frameworks like PyTorch, TensorFlow, and Hugging Face Transformers, along with proficiency in Python and distributed computing tools such as SLURM and Kubernetes.
Skills
Python
PyTorch
TensorFlow
Hugging Face Transformers
Kubernetes
SLURM
Docker
CI/CD
Prometheus
Grafana
PostgreSQL
Git
Jupyter Notebook
NVIDIA NeMo
NVIDIA Nemotron
Linux
AWS
Azure
Google Cloud Platform
What you'll do
Develop end-to-end AI solutions for enterprise use cases using NVIDIA AI models and libraries.
Tackle complex AI challenges across the entire model lifecycle, including training and optimization.
Support a broad portfolio of AI models spanning LLMs, multimodal data, and edge applications.
Collaborate with enterprise customers to understand their needs and deliver customized AI solutions.
Improve NVIDIA products by addressing scaling challenges at the intersection of computer architecture and AI.
Contribute expert knowledge to the organization through open-source projects, publications, and training.
What we're looking for
Strong foundational expertise in Engineering, Mathematics, Physics, Computer Science, or Data Science (BS, MS, Ph.D. or equivalent).
5+ years of hands-on experience with AI frameworks like PyTorch, JAX, TensorFlow and libraries such as Hugging Face Transformers.
Proficiency in Python programming, software design, debugging, and performance analysis within a Linux environment for at least 5 years.
Expertise in the full lifecycle of AI models including evaluation, failure analysis, pre-training, post-training, reinforcement learning, and optimization.
Experience with distributed computing methodologies and tools like SLURM and Kubernetes for training large models on GPUs.
Clear communication skills to collaborate effectively with executives and engineering teams.
Willingness and ability to solve complex problems by exploring unfamiliar territories.
Market check
Salary context
This
$152,000–$241,500
range sits above
48%
of similar postings on FindRole.
Peer median band
$161,350–$241,500
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$162,000–$241,962
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
801 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 797 roles with salary data.
Us, Ca, Santa Clara, US52 days ago
$152,000–$241,500
Python
TypeScript
Go
Rust
C++
Synthetic data generation
GPU-backed inference systems
Multi-agent workflows
Orchestration patterns
Complex long-running task systems
MCP
A2A-style communication patterns
Secure execution
Sandboxing
Secrets handling
Auditability
CI/CD