AI Engineer

- Develop and implement machine learning models using frameworks such as TensorFlow, Spark MLlib, and other AI tools to tackle various business challenges - Design scalable data pipelines and ETL processes to enable efficient data ingestion, transformation, and storage in either databases or big data environments - Conduct data mining and exploratory data analysis to extract insights and guide model development - Apply unsupervised learning techniques to discover patterns and anomalies in large datasets - Collaborate with cross-functional teams to embed AI solutions into existing systems and workflows - Optimize model training processes to enhance accuracy, efficiency, and readiness for deployment - Deploy machine learning models into production environments ensuring robustness and scalability - Utilize cloud platforms such as AWS for model training, deployment, and management of AI infrastructure - Implement natural language processing (NLP) applications to improve user interactions and automate content analysis - Maintain thorough documentation of algorithms, processes, and system architecture for transparency and reproducibility - Stay updated on emerging trends in AI research, quantum engineering, and big data technologies to continually enhance capabilities