Role ML/AI engineer
Location Princeton NJ - 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
Role ML/AI engineer Location Princeton NJ 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 u...
Role ML/AI engineer
Location Princeton NJ - 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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