Cloud Solutions Architect Position
6 days ago
About the Company
Our client is at the forefront of the AI revolution, providing cutting-edge infrastructure that's reshaping the landscape of artificial intelligence. They offer an AI-centric cloud platform that empowers Fortune 500 companies, top-tier innovative startups, and AI researchers to drive breakthroughs in AI. This publicly traded company is committed to building full-stack infrastructure to service the explosive growth of the global AI industry, including large-scale GPU clusters, cloud platforms, tools, and services for developers.
The Opportunity
As a Cloud Solutions Architect (Remote), you'll play a key role in designing, implementing, and maintaining large-scale machine learning (ML) training and inference workflows for clients. Working closely with a Solutions Architect and support teams, you'll provide expert, hands-on guidance to help clients achieve optimal ML pipeline performance and efficiency.
Key Responsibilities
- Design and implement scalable ML training and inference workflows using Kubernetes and Slurm, focusing on containerization (e.g., Docker) and orchestration.
- Optimize ML model training and inference performance with data scientists and engineers
- Develop and expand a library of training and inference solutions by designing, deploying, and managing Kubernetes and Slurm clusters for large-scale ML training with ready-to-deploy, standardized solutions
- Integrate with ML frameworks: integrate K8s and Slurm with popular ML frameworks like TensorFlow, PyTorch, or MXNet, ensuring seamless execution of distributed ML training workloads
- Develop monitoring and logging tools to track distributed training performance, identify bottlenecks, and troubleshoot issues
- Create automation scripts and tools to streamline ML training workflows, leveraging technologies like Ansible, Terraform, or Python
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