Description

You will design and implement end-to-end machine learning pipelines, covering data preprocessing, feature engineering, model training, evaluation, and deployment.

Responsibilities

• Develop and optimize ML/DL models for NLP, computer vision, and predictive analytics.
• Integrate AI models into production systems using APIs and cloud-native services.
• Conduct exploratory data analysis and derive actionable insights from complex datasets.
• Apply transfer learning and advanced techniques for image classification, object detection (YOLOv8), and generative AI (Stable Diffusion, SAM).
• Monitor model performance, retrain models, and manage versioning using MLOps best practices.

Required Skills

• 7+ years of professional experience in ML/AI engineering.
• Expert proficiency in Python and SQL.
• Strong command of OOPs principles.
• Hands-on experience with TensorFlow and Keras for DL model development.
• Experience implementing pipelines on AWS, Azure, or GCP.
• Proficiency in PySpark, NumPy, and pandas for data manipulation.
• Familiarity with model deployment frameworks like FastAPI or Flask.
• Experience with computer vision techniques, including YOLOv8.
• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field.

Key Skills

Education

Bachelor's or Master's degrees