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Cloud Native - Live Migration - Run GPU on Kubernetes

 

Architect needed for Series A Startup (team of 30)

 

100% Remote (in North America)

 

Equity participation

 

Base Salary: $200k-$300k

 

Key Responsibilities:

 

  • Drive native Kubernetes architectures.
  • Ensure Kubernetes-friendly installation and user experience.
  • Extend capabilities to support GPUs, TPUs, FPGAs, and other accelerators.
  • Collaborate with Product and Customers, acting as a technical translator to Product Management. Ensure appropriate prioritization of features and engage with customers during early evaluations and discussions to gather market insights.
  • Communication: Create detailed architecture diagrams, documents, and presentations.
  • Open Source Community: Stay actively involved with CNCF and related projects.
  • Enterprise-Class Solutions: Drive and deliver solutions for enterprise-class data, ML, and AI applications.
  • FinOps & SRE Best Practices: Implement FinOps for cloud financial management and modern SRE practices.

Qualifications:

 

  • Startup experience
  • Entrepreneurial mindset
  • 10+ years of infrastructure-level software architecture and development
  • Expertise in distributed systems
  • Proficiency with Linux and virtualization platforms
  • Native Kubernetes expertise
  • Experience with Kubernetes-based ML/AI systems (Kubeflow, Kueue, KServe, GPU Operators, DRA, Karpenter)

 

Deep Knowledge:

 

  • ML/AI use cases and customer stories of model development, training, inference, and hardware accelerator usage
  • Proven track record of delivering complex distributed systems
  • Involvement in CNCF or similar communities
  • 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 a related field
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