AI / ML Developer

About this role

We are looking for an experienced AI / Machine Learning Developer to design, develop, and implement intelligent solutions supporting advanced analytics, predictive modeling, and business process automation. The role focuses on building scalable AI/ML models, developing data-driven applications, and integrating machine learning capabilities with enterprise platforms, including AFP-related systems and workflows. Working closely with data engineers, solution architects, and business stakeholders, the developer ensures reliable model performance, seamless integration, and alignment with business requirements and technical standards.

Key Responsibilities Design, develop, and deploy AI and Machine Learning models to support predictive analytics, forecasting, and business decision-making. Develop and optimize machine learning algorithms, including regression, classification, clustering, and time-series forecasting. Build and maintain data preprocessing, feature engineering, model training, and evaluation pipelines. Implement AI/ML integrations with AFP-related applications, enterprise data platforms, and business planning systems.

Develop APIs and integration components to enable seamless communication between AI/ML models and existing applications. Collaborate with data engineers and technical teams to ensure data availability, quality, and efficient processing. Monitor and optimize model accuracy, performance, scalability, and reliability in production environments. Support testing, troubleshooting, deployment, and continuous improvement of AI/ML solutions.

Translate business requirements into technical AI/ML solutions while maintaining development standards and documentation. Strong hands-on experience in AI/ML development , including model design, training, deployment, and optimization. Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Solid understanding of machine learning algorithms, statistical modeling, predictive analytics, and forecasting techniques.

Experience developing data pipelines, performing feature engineering, and working with structured and unstructured datasets. Knowledge of REST APIs, system integration, and connecting AI/ML solutions with enterprise applications. Experience with cloud-based AI/ML platforms such as Azure Machine Learning, AWS SageMaker, or Google Vertex AI. Understanding of MLOps concepts, including model versioning, monitoring, automated deployment, and CI/CD pipelines.