Simplify Orchestration & Optimization for AI Accelerators 

Drive Software Architecture to Achieve Scalable AI ops 

Achieve up to 70% GPU utilization.

• US based startup (series A)
• Company Size: 30
• 100% REMOTE (in North America)
• Compensation: Base Salary 200k - 300k + Equity

Key Responsibilities:

• GPU Optimization for ML/AI: Lead the continued expansion into GPU optimization for ML/AI workloads.
• Design and deliver Autonomous Cloud Optimization product
• Port architecture to Kubernetes
• Established product architecture and development plans.
• Customer and Sales Support: Provided training and documentation to support sales and customers.

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.