Description

Key Skills: Machine Learning Operations (MLOps), Artificial Intelligence, Generative AI, Deep Learning, TensorFlow, PyTorch, Cloud Platforms (AWS/Azure/GCP), Feature Engineering, Data Preprocessing, Git, Neural Networks, Chatbots

Roles & Responsibilities:

• Design, develop, and implement AI/ML applications and production-ready systems.
• Build and maintain scalable Machine Learning Operations (MLOps) pipelines.
• Develop and integrate AI models including Generative AI, deep learning, and neural network solutions.
• Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.
• Design and optimize machine learning models and algorithms for business use cases.
• Perform data preprocessing, feature engineering, and model performance optimization.
• Deploy, monitor, and maintain AI/ML models in cloud or on-premise environments.
• Participate in technical discussions and contribute to solution design and problem-solving activities.
• Support continuous improvement and innovation initiatives within AI projects.
• Maintain code quality and version control practices using Git.

Experience:

• 4 - 9 years of relevant experience in AI/ML Engineering and Machine Learning Operations (MLOps).
• Strong hands-on experience with Machine Learning Operations practices and deployment pipelines.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud.
• Strong understanding of deep learning frameworks such as TensorFlow and PyTorch.
• Experience in data preprocessing and feature engineering techniques.
• Hands-on experience with Generative AI models and AI application development is preferred.
• Strong understanding of neural networks, chatbots, and image processing concepts.
• Experience with version control tools such as Git.

Education: Any Graduation

Key Skills

Education

Any Graduate