Solutions Architect - Deep Neural Network Evaluation
Pubblicato il 17-09-2026 - NVIDIA in Pescara
Overview
Possiede le competenze per ricoprire questo ruolo? Legga i dettagli completi qui sotto e invii la sua candidatura oggi stesso.
As an AI-focused Solutions Architect, you will be the technical bridge between NVIDIA and our customers, driving evaluation and design of agentic AI systems. You'll work across ELAA to benchmark, refine, and deploy LLMs, VLMs, and embedding models, shaping how enterprises leverage NVIDIA technologies. You'll lead proof-of-concept demonstrations and collaborate with cross-functional teams to deliver robust, end-to-end AI pipelines.
This role combines hands-on neural network work with strategic customer engagement to scale AI adoption.
Retribuzione / Benefits
- comprehensive benefits package
- competitive salary
Responsabilità
- Engage with key customers to understand their needs and architect tailored AI solutions
- Drive adoption of NVIDIA open-source evaluation tools (NeMo) and standard methodologies for model robustness
- Develop and demonstrate solutions using NVIDIA and open-source LLMs, integrating into agentic pipelines
- Collaborate with engineering, product,
and sales to plan optimal customer-focused solutions
- Enable product feature growth through customer feedback and proof-of-concept evaluations
- Build domain expertise and contribute to Enterprise Computing architectures using NVIDIA technology
Requisiti fondamentali
- 5+ years hands-on experience building and evaluating Deep Neural Networks
- Proven experience in ML/DL/Datascience with emphasis on deep learning
- Knowledge of latest LLMs, VLMs, and retrieval systems xkiyazw
- Familiarity with libraries for DNN evaluation like Eval Harness or NVIDIA Evaluation Microservice
- Understanding of modern evaluation benchmarks and capability to extend or create benchmarks
- Excellent English communication and presentation skills
- strong communication
- cross-functional collaboration
- customer-facing presentation
- Neural network development and fine-tuning
- LLMs, VLMs, and embedding models
- Retrieval systems and pipelines