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$300,000 - $400,000 / yr
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Vancouver, BC
IDj-6932Posted 12/19/2024
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 $300k - 360k + CAD, 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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