Chief Architect - ML on K8s - AI Enabled Orchestration Platform - Remote
Living Talent Company
Date: 1 week ago
City: Silver Spring, MD
Salary:
$250,000
-
$350,000
per year
Contract type: Full time
Remote
Kubernetes based Cloud Native Orchestration Platform with GPU Capabilities
Startup (revenue-generating, Series A)
Startup (revenue-generating, Series A)
- Company size: 40
- Future unicorn
- REMOTE first culture
- Smart, fun, low-ego team culture
- Compensation: Base Salary 250k++, Equity
- Extending capabilities beyond the current CPU optimization into GPU optimization.
- Develop capabilities to help customers rapidly set up ML Environment
- Architecture & Development: Kubernetes-based ML/AI platform.
- Leadership & Collaboration: with C-staff, product management, engineering, and design partners.
- Communication: Create detailed architecture diagrams, documents, and presentations.
- Focus on the User Experience (K8s users, Infrastructure Admin, MLOps staff, etc).
- 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.
- Entrepreneurial, Startup Experience
- 10 years+ infrastructure level software architecture and development.
- Linux, Virtualization platforms (hands-on)
- AWS, GCP or Azure.
- Kubernetes-based ML/AI systems (Kubeflow, Kueue, KServe, GPU Operators, DRA, Karpenter)
- 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.
- 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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