AI Engineer - Python/Machine Learning

Key Tasks and Accountabilities :

• Design, develop, and maintain end-to-end software solutions using generative AI technologies and machine learning within the logistics technology department.

• Utilize low/no-code tools as accelerators for development and solution implementation.

• Integrate and work with SAP systems to ensure seamless data flow between procurement and logistics operations.

• Develop and deploy applications using Python and Machine Learning (ML) stack to automate invoice validation, anomaly detection, and data analysis.

• Collaborate with cross-functional teams to gather requirements, propose technical solutions, and align deliverables with business needs.

• Implement and maintain deployment pipelines, leveraging Azure DevOps for CI/CD automation.

• Ensure solutions meet compliance, security, and performance standards.

• Conduct code reviews and enforce best practices in software engineering.

• Document technical designs, workflows, and processes for both technical and non-technical stakeholders.

• Support and troubleshoot production issues, ensuring minimal downtime and quick resolution.

Technical Stack :

• Python, TensorFlow, PyTorch, Scikit-learn, Docker, Kubernetes, Azure, CI/CD, SAP, Model Context Protocol (MCP).

Mandatory Skills :

• Strong proficiency in Python and experience with ML frameworks.

• Experience with Model Context Protocol (MCP) for managing context in ML-driven applications.

• Familiarity with containerization (Docker, Kubernetes).

• Experience in application development and deployment in production environments.

• Experience with cloud platforms (preferably Azure).

• Strong problem-solving skills and ability to work with large datasets.

• Excellent communication skills; proficient in English (written and spoken).

• Ability to work collaboratively in a fast-paced, agile environment.

• Participate in and promote collaboration, sharing knowledge and best practices.

• Consistently apply compassionate communication in the professional environment.

• Present technical content to leadership and other stakeholders in fluent English.