AI/ML Engineer

AI/ML Engineer

Key Responsibilities:

• Design and implement machine learning models and algorithms for various use cases (e.g., prediction, classification, NLP, computer vision).
• Analyze and preprocess large datasets to build robust training pipelines.
• Conduct research to stay up to date with the latest AI/ML advancements and integrate relevant techniques into projects.
• Train, fine-tune, and optimize models for performance and scalability.
• Deploy models to production using tools such as Docker, Kubernetes, or cloud services (AWS, GCP, Azure).
• Collaborate with software engineers, data scientists, and product teams to integrate AI/ML solutions into applications.
• Monitor model performance in production and continuously iterate for improvements.
• Document design choices, code, and models for transparency and reproducibility.

Preferred Qualifications:

• Knowledge in

  NLP, LLM and GenAI.

• Preferred experience in

  Real Image Processing, and RAG-oriented

  .
• Knowledge in deep learning architectures such as CNNs, RNNs, transformer models.
• Experience with NLP libraries (e.g., Hugging Face Transformers, spaCy) or computer vision tools (e.g., OpenCV).
• Background in deep learning architectures such as CNNs, RNNs, GANs, or transformer models.
• Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker).
• Contributions to open-source AI/ML projects or publications in relevant conferences/journals.