Key Responsibilities :AI Model Development :Design, develop, and implement AI models using Python and machine learning frameworks like TensorFlow , Keras , PyTorch , or Scikit-Learn .Create algorithms and models for a wide range of AI applications, such as natural language processing (NLP) , image recognition , recommendation systems , and predictive analytics .Work with large datasets, data preprocessing , and feature engineering to prepare data for training and model validation.Machine Learning and Deep Learning :Apply supervised and unsupervised learning techniques to solve problems in areas such as customer segmentation, anomaly detection, and forecasting.Implement and fine-tune deep learning models for complex tasks such as image classification, computer vision , and natural language understanding .Experiment with cutting-edge models like transformers (e.g., BERT , GPT ), CNNs , and RNNs .Model Optimization and Tuning :Optimize model performance using techniques such as hyperparameter tuning , model ensembling , and cross-validation .Assess and enhance the accuracy , precision , and recall of models to ensure high-quality predictions.Implement techniques for model deployment , including containerization using Docker or deploying models as REST APIs for integration.AI System Integration :Integrate AI models and machine learning algorithms into existing business systems and applications.Work closely with software engineers and IT teams to deploy and scale AI solutions.Design and develop data pipelines to automate the flow of data to and from AI systems.Research & Innovation :Stay up to date with the latest trends, methodologies, and advancements in AI, machine learning, and data science.Conduct research and proof-of-concept experiments to explore new techniques and technologies that could benefit the organization.Contribute to technical publications, blogs, and whitepapers on AI-related topics.Collaboration & Support :Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and business analysts.Provide AI expertise and support for troubleshooting, optimization, and performance monitoring.Assist in training and mentoring junior AI developers and other team members.Documentation & Reporting :Document AI models, codebases, and methodologies for future reference and maintenance.Generate reports and visualizations to present model performance and results to stakeholders and leadership.Required Qualifications :
- 3-5 years of professional experience in Python programming and AI / ML development .
- Strong knowledge of AI and machine learning concepts such as classification , regression , clustering , deep learning , and reinforcement learning .
- Hands-on experience with popular machine learning libraries like Scikit-Learn , TensorFlow , Keras , PyTorch , XGBoost , or LightGBM .
- Proficiency in data manipulation and preprocessing using libraries like Pandas , NumPy , and SciPy .
- Experience working with deep learning frameworks (e.g., TensorFlow , Keras , PyTorch ).
- Strong understanding of neural networks , CNNs , RNNs , and transformer-based models (e.g., BERT , GPT ).
- Solid experience in model evaluation and performance metrics such as accuracy , precision , recall , F1-score , and AUC .
- Familiarity with NLP techniques (e.g., text preprocessing , sentiment analysis , text classification ) is a plus.
- Experience in cloud platforms like AWS , Azure , or Google Cloud for deploying AI models at scale.
Skills Required
Tensorflow, Keras, Pytorch, XGBoost