About the role
Responsibilities:
- Develop, train, and deploy machine learning models using Amazon SageMaker.
- Build and maintain scalable, production-ready ML pipelines.
- Perform data preprocessing, feature engineering, model evaluation, and optimization.
- Deploy and monitor ML models in production environments.
- Integrate Generative AI models into AI/ML applications where required.
- Collaborate with cross-functional teams and provide technical solutions.
- Mentor junior team members and contribute to technical decisions.
- Improve model performance, scalability, reliability, and deployment efficiency.
Requirements:
- Minimum 5 years of hands-on experience with Amazon SageMaker.
- Strong experience in machine learning development and production deployment.
- Understanding of cloud computing, data processing, and model optimization.
- Experience building end-to-end AI/ML solutions.
- 15 years of full-time education.
- Must-Have Skills: Amazon SageMaker, Machine Learning Model Development and Deployment, ML Pipeline Development and MLOps, Python, and Cloud-Based AI/ML Solutions.
- Good-to-Have Skills: TensorFlow or PyTorch, generative AI and large language models (LLMs), deep learning and neural networks, AWS AI/ML services, MLOps, and model monitoring.