Demo

Cloud Native AI Architect - Kubernetes - Startup (Remote)

Living Talent Company
Chicago, IL Remote Full Time
POSTED ON 1/25/2025
AVAILABLE BEFORE 4/21/2025

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.
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