Solutions Architect: GPU-Accelerated Data for LLMs

Salary: CHF 155'000 - 195'000 per year

Requirements:

• Track record in fields related to machine learning focused data processing and analytics.
• Experience with one of the following libraries: Pandas, NumPy, Numba, Ibis, Dask, Spark, and their GPU accelerated counterparts (cuDF, cuGraph, cuNumeric, CuPy, etc.).
• High level understanding of one of modern AI fields (NLP, CV, ASR, TTS, etc.).
• Excellent verbal, written communication, and technical presentation skills in English.
• 5+ years work or research experience with Python, C++, or other software development.
• MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields.
• Ability to work with multiple levels and teams across organizations, including Engineering, Product, Sales, and Marketing.
• Ability to work in a constantly evolving technological environment without losing focus.
• Ability to multitask effectively in a fast-paced environment.
• Strong analytical and problem-solving skills.
• Strong time-management and organization skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into very complex projects.
• Self-starter with an attitude for growth, passion for continuous learning, and sharing findings across the team.
• Experience in very large-scale dataset preparation and curation.
• Prior experience working with AI/NLP focused datasets in a wide range of formats including tabular, textual, audio, and proprietary file formats (e.g. PDF).
• Experience using DevOps technologies such as Docker, Kubernetes, Singularity, etc.

Responsibilities:

• Work directly with key customers to understand their technology and suggest and develop optimized approaches to the problems they are currently solving.
• Develop and demonstrate solutions based on NVIDIAs frameworks, such as RAPIDS and its integration with DASK as well as GPU accelerated Spark.
• Support customers in adoption of the NVIDIA GPU-accelerated data science libraries, including their application for generation of LLM training and RAG inference datasets.
• Perform in-depth analysis and optimization to ensure the best performance on GPU-based systems, including support in optimization of both training and inference data ingestion pipelines.
• Partner with Engineering, Product, and Sales teams to plan and develop the best solutions for customers.
• Enable development and growth of product features through customer feedback and proof-of-concept evaluations.
• Build industry expertise and become a contributor in integrating NVIDIA technology into Enterprise Computing architectures.
• Dynamically engage with developers, scientific researchers, data scientists, IT managers, and senior leaders.
• Drive relationships with key executives and managers to evangelize the adoption of NVIDIA-based AI technology.

Technologies:

• AI
• Architect
• DevOps
• Docker
• Support
• Kubernetes
• LLM
• Machine Learning
• Marketing
• Python
• Spark
• numpy
• pandas

More:

We are NVIDIA, and we are looking for a Solutions Architect to serve as the first line of technical expertise between us and our customers. In this role, we work across a range of partners and technologies, supporting proof-of-concept demonstrations, customer adoption, and enterprise integration of our AI technology. You will collaborate with Engineering, Product, Sales, and Marketing teams in a fast-paced, evolving environment, with opportunities to build deep industry expertise and contribute to the growth of our products and solutions.

last updated 27 week of 2026