AI/ML Engineer

As an AI/ML Engineer, you will be responsible for designing, developing, and deploying machine learning models and AI-driven solutions to enhance business processes and product capabilities. Your expertise in data science, algorithm development, and software engineering will be crucial in solving complex problems using cutting-edge technologies. Key Responsibilities: - Model Development: Build, train, and optimize machine learning models for predictive analytics, natural language processing, computer vision, and other AI applications. - Data Engineering: Preprocess, clean, and structure large datasets for model training and evaluation. - Deployment & Integration: Implement ML models into production systems using scalable frameworks and APIs. - Research & Innovation: Stay updated with the latest AI/ML trends and incorporate best practices into solutions. - Performance Monitoring: Continuously monitor and improve model accuracy, efficiency, and robustness. - Collaboration: Work closely with cross-functional teams including software engineers, product managers, and data analysts to deliver AI-driven features. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Data Science, or related field. - Strong proficiency in Python, Tensor Flow, PyTorch, and ML libraries. - Experience with data pipelines, feature engineering, and model deployment. - Knowledge of cloud platforms (Azure, AWS, GCP) and containerization (Docker, Kubernetes). - Familiarity with MLOps practices and CI/CD pipelines. - Excellent problem-solving and analytical skills. Additional Company Details: The company values staying at the forefront of AI/ML trends and encourages responsible AI practices. They foster a collaborative environment where cross-functional teamwork is essential for success. As an AI/ML Engineer, you will be responsible for designing, developing, and deploying machine learning models and AI-driven solutions to enhance business processes and product capabilities. Your expertise in data science, algorithm development, and software engineering will be crucial in solving complex problems using cutting-edge technologies. Key Responsibilities: - Model Development: Build, train, and optimize machine learning models for predictive analytics, natural language processing, computer vision, and other AI applications. - Data Engineering: Preprocess, clean, and structure large datasets for model training and evaluation. - Deployment & Integration: Implement ML models into production systems using scalable frameworks and APIs. - Research & Innovation: Stay updated with the latest AI/ML trends and incorporate best practices into solutions. - Performance Monitoring: Continuously monitor and improve model accuracy, efficiency, and robustness. - Collaboration: Work closely with cross-functional teams including software engineers, product managers, and data analysts to deliver AI-driven features. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Data Science, or related field. - Strong proficiency in Python, Tensor Flow, PyTorch, and ML libraries. - Experience with data pipelines, feature engineering, and model deployment. - Knowledge of cloud platforms (Azure, AWS, GCP) and containerization (Docker, Kubernetes). - Familiarity with MLOps practices and CI/CD pipelines. - Excellent problem-solving and analytical skills. Additional Company Details: The company values staying at the forefront of AI/ML trends and encourages responsible AI practices. They foster a collaborative environment where cross-functional teamwork is essential for success.