Job Description

Running ML and GPU loads on Native Kubernetes in the Cloud

Effective Resource Optimization: DRA and GPU Fractionalization

• Startup (Series A, team of 40)
• REMOTE first
• Smart, fun, low-ego team culture
• Compensation: Base Salary 250k+, Equity

Key Responsibilities:

• Architecture & Development: Kubernetes-based ML/AI optimization platform
• Leadership & Collaboration: with C-staff, product management, engineering, and design partners.
• Communication: Create detailed architecture diagrams, documents, and presentations.
• User Experience Focus: for Infrastructure Admin and MLOps staff.
• Open Source Community: Stay actively involved with CNCF and related projects.
• Enterprise-Class Solutions: Drive & deliver solutions for enterprise-class data, ML, AI applications.
• FinOps & SRE Best Practices: FinOps for cloud financial management, modern SRE practices.

Qualifications:

• Entrepreneurial, Startup Experience
• 10 years+ infrastructure level software architecture and development.
• Deep - Native Kubernetes Expertise
• Modern Cloud Architecture
• Linux, Virtualization platforms (hands-on)
• Kubernetes-based ML/AI systems (Kubeflow, Kueue, KServe, GPU Operators, DRA, Karpenter)

Deep knowledge:

• ML/AI use cases & customer stories of model development, training, inference
• Hardware accelerator usage (CPU, GPU, TPU).
• Proven track record of delivering complex distributed systems.
• Active involvement in open-source communities - CNCF projects.
• Strong leadership and team collaboration skills.
• Excellent communication skills, both verbal and written.

Preferred Qualifications:

• Knowledge of additional ML/AI frameworks and tools.
• Experience in DevOps practices and tools.
• Certification in Kubernetes or related technologies.
• Awareness of FinOps and SRE best practices
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Job Tags

Similar Jobs