Experience 3–6 yrs (5+ years)
About the role
structured by ORIWe are looking for an experienced AI/ML Engineer with 5+ years of hands-on experience in developing, deploying, and monitoring machine learning models in production environments. The ideal candidate should have strong expertise in Python, Scikit-learn, TensorFlow/PyTorch, and AWS SageMaker.
What you will do
- Own and deliver multiple AI/ML use cases from development to production.
- Design, train, deploy, and monitor ML models using AWS SageMaker.
- Analyze large-scale datasets and generate actionable insights.
- Support advanced analytics and business use cases.
- Follow MLOps practices to ensure reliable and scalable model deployment.
What they are looking for
- 5+ years of AI/ML experience with production deployment exposure.
- Strong Python and AWS SageMaker skills.
- Proven end-to-end ML model development experience.
- Strong analytical and problem-solving skills.
PythonScikit-learnTensorFlowPyTorchMLOpsMachine LearningAdvanced AnalyticsAWS SageMakerAWS
Full posting text
We are looking for an experienced AI/ML Engineer with 5+ years of hands-on experience in developing, deploying, and monitoring machine learning models in production environments. The ideal candidate should have strong expertise in Python, Scikit-learn, TensorFlow/PyTorch, and AWS SageMaker.
Key Responsibilities
- Own and deliver multiple AI/ML use cases from development to production.
- Design, train, deploy, and monitor ML models using AWS SageMaker.
- Analyze large-scale datasets and generate actionable insights.
- Support advanced analytics and business use cases.
- Follow MLOps practices to ensure reliable and scalable model deployment.
Requirements
- 5+ years of AI/ML experience with production deployment exposure.
- Strong Python and AWS SageMaker skills.
- Proven end-to-end ML model development experience.
- Strong analytical and problem-solving skills.
Skills: aws,sagemaker,python
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