Solutions Architect, AI and ML

Description

The company is building a leading AI business, and this role helps customers adopt GPU hardware and software and build and deploy machine learning, deep learning and data analytics solutions on major cloud platforms.

The Solutions Architect team works with cutting-edge computing hardware and software, including recent advances in machine learning and data science.

You are the first technical point of contact between the company and its customers. You work directly with developers, researchers and data scientists at some of the company's most strategic technology customers, and with business and engineering teams on product strategy.

You will shape end-to-end technical solutions that use the company's full technology range to meet customers' business needs.

Responsibilities

• Work with cloud service providers to build and demonstrate solutions using the company's ML, DL and data science software and hardware.
• Build and deploy AI and ML solutions at scale on cloud GPU platforms using the company's AI software.
• Create custom proofs of concept that address customers' critical business needs with the company's hardware and software.
• Work with Sales Account Managers or Developer Relations Managers to find and win new business for the company's ML, DL and other software products and solutions.
• Prepare and deliver technical content for customers, such as presentations on purpose-built solutions and workshops on the company's products.
• Hold regular technical meetings with customers covering project and product roadmaps, feature discussions and introductions to new technologies. Build close technical relationships so customer issues get resolved quickly.

Requirements

• At least 4 years in solutions engineering or a similar sales engineering role.
• At least 3 years of work experience in deep learning and machine learning. Experience with TensorFlow or PyTorch is required, and GPU and CUDA experience is extremely helpful.
• A BS, MS or PhD in electrical or computer engineering, computer science, statistics, physics or another engineering field, or equivalent experience.
• A proven record of deploying solutions on AWS, GCP or Azure.
• Knowledge of DevOps and ML Ops tools such as Docker, containers, Kubernetes and data center deployments.
• Ability to use at least one scripting language, such as Python.
• Solid programming and debugging skills.
• Ability to explain your ideas and code clearly in documents, presentations and other formats.
• Nice to have: AWS, GCP or Azure Professional Solutions Architect certification.
• Nice to have: hands-on experience with the company GPUs and SDKs such as CUDA, RAPIDS and Triton.
• Nice to have: system-level experience with GPU-based systems.
• Nice to have: experience with deep learning at scale.
• Nice to have: familiarity with parallel programming and distributed computing platforms.

Conditions

Most work is done through conferencing tools, but occasional travel is required for on-site visits to customers and industry events.

Base salary depends on location, experience and the pay of employees in similar roles. The base range is 152,000 USD to 241,500 USD for Level 3, and 184,000 USD to 287,500 USD for Level 4.

Applications will be accepted at least until October 27, 2026.

This posting is for an existing vacancy.

The company uses AI tools in its recruiting processes.

The company is committed to an inclusive workplace and is an equal opportunity employer.