Job Summary: We are seeking an experienced AI Engineer to join our tech team and develop cutting-edge artificial intelligence solutions. You will work closely with data scientists, software engineers, and product managers to design, develop, and deploy AI-powered applications that enhance business processes and user experiences. Key Responsibilities: Develop AI Models: Design, train, and optimize machine learning (ML) and deep learning (DL) models for real-world applications. Data Processing: Collect, clean, and preprocess large datasets for AI model training and evaluation. Algorithm Development: Implement AI-driven solutions for tasks like computer vision, NLP, recommendation systems, and predictive analytics. Model Deployment: Deploy AI models in production environments using cloud platforms (AWS, GCP, Azure) and ML frameworks (TensorFlow, PyTorch). Performance Optimization: Continuously monitor and improve AI models for efficiency, scalability, and accuracy. Collaboration: Work with cross-functional teams, including software developers and product managers, to integrate AI into company products. AI Research & Innovation: Stay updated with the latest advancements in AI and apply innovative approaches to improve existing solutions. Required Qualifications: Education: Bachelor's or Master’s in Computer Science, AI, Data Science, or a related field (Ph.D. is a plus). Experience: 2+ years of experience in AI/ML engineering, with hands-on experience in developing and deploying AI models. Programming Skills: Proficiency in Python, R, or Java, with experience in ML libraries like TensorFlow, PyTorch, Scikit-learn. Cloud & DevOps: Experience with cloud-based AI services (AWS SageMaker, Google AI, Azure ML) and containerization (Docker, Kubernetes). Big Data & Databases: Knowledge of SQL/NoSQL databases, data pipelines, and distributed computing frameworks (Hadoop, Spark). AI Ethics & Bias Mitigation: Understanding of responsible AI principles and best practices. Preferred Qualifications: Experience with real-time AI applications (e.g., chatbots, autonomous systems). Knowledge of MLOps, CI/CD for AI pipelines. Familiarity with edge AI and IoT-based AI applications.