Chief Architect AI / ML Infrastructure Cloud Cost Optimization & Resource Utilization
Make your application after reading the following skill and qualification requirements for this position.
- Startup (revenue-generating, Series A)
- Company size : 30
- Future unicorn
- REMOTE first culture
- Smart, fun, low-ego team culture
- Compensation : Base Salary 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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Remote working / work at home options are available for this role.
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