Who you are
- Enrolled in or recently completed a degree in Computer Science, AI, or a related field.
- Hands-on experience with Kubernetes, container orchestration, and cloud-native infrastructure.
- Knowledge of RL algorithms, decision trees, and multi-objective optimization.
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and model-serving tools (e.g., TensorFlow Serving, TorchServe).
- Strong programming skills in Python; familiarity with Go is a plus.
- Knowledge of RL applications in scheduling and resource management for AI workloads is an advantage.
How to Apply:
- Submit your resume, a brief cover letter, and a link to your GitHub profile. In your cover letter, explain your interest in AI-powered Kubernetes scheduling and highlight any relevant experience.
- Deadline 6th of November.
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