Machine Learning Engineer

• Design and implement scalable infrastructure for training, fine-tuning, and serving open source LLMs (Llama, Mistral, Gemma, etc.)
• Architect and manage Kubernetes clusters for ML workloads, including GPU scheduling, autoscaling, and resource optimization
• Design, implement, and maintain feature stores for ML model training and inference pipelines
• Build and optimize LLM inference systems using frameworks like vLLM, TensorRT-LLM, and custom serving solutions
• Ensure 99.9%+ uptime for ML platforms through robust monitoring, alerting, and incident response procedures
• Design and implement ML platforms using DataRobot, Azure Machine Learning, Azure Kubernetes Service (AKS), and Azure Container Instances
• Develop and maintain infrastructure using Terraform, ARM templates, and Azure DevOps
• Implement cost-effective solutions for GPU compute, storage, and networking across Azure regions
• Ensure ML platforms meet enterprise security standards and regulatory compliance requirements

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