Solutions Architect, CSP GTM

This is a fully remote position, open to applicants in France, +1 more country.

📋 Description

• Create and showcase solutions utilizing NVIDIA GenAI software and hardware technologies in collaboration with hyperscaler partners for developers.

• Collaborate closely with major clients and hyperscaler partners to identify challenges and propose solutions leveraging NVIDIA products.

• Assess and enhance GPU-accelerated systems by utilizing NVIDIA software platforms, focusing on training and inference pipelines.

• Collaborate with Engineering, Product, and Sales teams to devise appropriate solutions.

• Drive product feature development and expansion through customer insights and proof-of-concept evaluations.

• Cultivate industry expertise and aid in the integration of NVIDIA technology into enterprise computing architectures.

• Execute proof-of-concept demonstrations.

• Foster relationships with technical executives and managers to promote accelerated computing and Generative AI.

• Interact with developers, researchers, data scientists, IT managers, and senior leadership.

⛳️ Requirements

• Over 5 years of experience as a Solutions Architect/Engineer or in a related role within AI-focused fields.

• Strong verbal and written communication abilities; adept at presenting technical solutions in English.

• Proficiency in deploying large-scale training and inference pipelines on hyperscaler infrastructure, particularly with GCP.

• MS/PhD or equivalent in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, or a related engineering field.

• Demonstrated academic and/or industry experience in machine learning, deep learning, and/or data science.

• Capability to collaborate across Engineering, Product, Sales, and Marketing teams.

• Proactive self-starter with a passion for growth, continuous learning, and disseminating knowledge within the team.

• Experience with hyperscaler platforms, particularly GCP.

• Background in executing and optimizing distributed deep learning training at scale.

• Familiarity with optimizing inference pipelines, including aspects like model compression, compilation, or serving.

• Experience with larger transformer-based architectures.

• Knowledge of DevOps technologies such as Docker, Kubernetes, and Singularity.

🏝️ Benefits

• Comprehensive health and wellness programs.

• Opportunities for professional development and continuous learning.

• Flexible work arrangements to support work-life balance.

• Engaging and inclusive company culture.

• Access to cutting-edge technology and tools.