Artificial Intelligence Engineer - Machine Learning Models

Key Responsibilities :

- Design, develop, and optimize machine learning and AI models for classification, regression, and recommendation systems

- Build and maintain end-to-end machine learning pipelines, from data preprocessing to model deployment

- Develop and fine-tune deep learning architectures using frameworks like TensorFlow and PyTorch

- Apply MLOps best practices for model versioning, monitoring, and retraining

- Work with large-scale datasets, performing feature engineering and data augmentation

- Optimize model performance for scalability, latency, and production readiness

- Deploy AI models using containerization (Docker) and cloud platforms such as Azure

- Research and implement cutting-edge AI techniques to improve existing systems and integrate them into production

- Collaborate with data scientists, engineers, and product teams to integrate AI capabilities into real-world applications

Requirements :

- Strong programming skills in Python

- Hands-on experience training and deploying machine learning models in production environments

- Proficiency with ML/AI libraries and frameworks such as TensorFlow, PyTorch, Hugging Face, and scikit-learn

- Familiarity with cloud platforms such as AWS, GCP, or Azure, and MLOps tools

- Solid understanding of data structures, algorithms, and performance optimization techniques

- Experience in data engineering, feature extraction, and model evaluation

- Working knowledge of deep learning techniques such as CNNs, RNNs, Transformers, and GANs

- Experience with large language models (LLMs) such as GPT, BERT, LLaMA, or T5, including fine-tuning and deployment

- Understanding of multi-modal AI involving text and image processing