Chief Architect - Kubernetes & Cloud Orchestration - GPU Workloads (Remote)

Living Talent Company


Date: 3 weeks ago
City: Remote, Remote
Contract type: Full time
Remote
Autonomous Cloud Orchestration Software

Optimize CPU & GPU

K8s Control Layer

  • Startup (revenue-generating, Series A)
  • Company size: 30
  • Future unicorn
  • REMOTE first culture
  • Smart, fun, low-ego team culture
  • Compensation: Base Salary US $250k+, Equity

Key Responsibilities

  • Architecture & Development: Kubernetes-based ML/AI optimization platforms
  • 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.

Extensive Experience

  • Linux, Virtualization platforms (hands-on)
  • AWS, GCP or Azure.

Strong Experience

  • 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).
  • Modern cloud-native architectures (scalability, availability, reliability, security, observability).
  • Proven track record of delivering complex distributed systems.
  • Active involvement in open-source communities, particularly CNCF and related 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.

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