Overview
Pay Range: $70hr - $75hr
Responsibilities
Design, develop, and implement machine learning and deep learning models.
Preprocess and analyze large-scale structured and unstructured datasets.
Optimize models for performance, scalability, and efficiency.
Integrate models into production systems using APIs or cloud-based deployment.
Monitor, test, and retrain models as required based on feedback and performance.
Document model development, architecture, and performance metrics.
Design scalable infrastructure for training, deploying, and monitoring ML and LLM models in production.
Manage Azure Kubernetes Service (AKS) clusters and containerized ML workloads.
Ensure model governance, versioning, and reproducibility using tools like MLflow and Azure DevOps.
Experience with Azure Machine Learning, Azure OpenAI, Azure DevOps, and AKS.
Proficiency in Python, Docker, Kubernetes, and CI/CD pipelines.
Experience with LLM fine-tuning, prompt engineering, and model deployment.
Familiarity with MLflow, Terraform, and monitoring tools like Prometheus/Grafana.
Collaborate with data scientists and domain experts to understand project objectives and define modeling approaches.
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