Senior Solution Architect, MLOps - AI Factory
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Job description
We are looking for an AI Factory Solution Architect. NVIDIA is at the forefront of the AI computing revolution, building innovative deep learning solutions that reshape industries worldwide. In this role, you will play a key role in introducing our advanced GPU products to deployments across data centers. If you enjoy system building and have a demonstrable track record of technical customer interactions, this is a prime opportunity to make a meaningful contribution.
What You'll Be Doing:
- Help architect and scale high-performance, distributed AI infrastructure on-prem or in the cloud, built with the latest NVIDIA GPU supercomputers for new and existing customers.
- Be a motivating leader in integrating NVIDIA technology into HPC architectures to support scientific and engineering applications.
- Be an internal champion for Deep Learning and Infrastructure among the NVIDIA technical community.
- Support Development activities and engage in POCs/POVs to validate new features, and architectures.
- Develop solutions and showcase the AI ecosystem.
What We Need To See:
- B.sc or M.sc in Engineering, Mathematics, Physics, or Computer Science or equivalent experience.
- 5+ years in software development or ML engineering.
- Extensive ability to solve problems within the customer infrastructure.
- Practical expertise with on-premises Kubernetes (K8S) infrastructure-orchestration and platform.
- Experience working with containers and MLOps tools.
- Background with modern Deep Learning software architecture and frameworks including PyTorch, vLLM and TritonServer.
- Capable of working in a constantly evolving environment without losing focus.
- Committed with 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.
Ways To Stand Out From The Crowd:
- Technical knowledge of developer digital platforms and their trends.
- Experience working with Nvidia operators.
- Expertise in operating Kubernetes, as well as experience writing or customizing Kubernetes configurations.
- Background in deploying large-scale multi-node training and inferencing pipelines.
- Good presentation skills
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you.
Originally posted on Himalayas
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