AI/ML Engineer at Cargill, Bengaluru/Bangalore
Job Purpose and Impact: As an AI Engineer at Cargill, you will be instrumental in designing and developing AI-driven solutions to elevate our Data Management and Data Governance capabilities. Leveraging machine learning, generative AI, and automation, your work will focus on enhancing data quality, improving metadata management, refining master data practices, automating data classification, and streamlining governance workflows. The ultimate goal is to ensure that Cargill's data is trustworthy, compliant, and readily available for business insights. You will foster close collaboration with Data Engineering, Data Domain & Governance, Architecture, Security, and various Business/Function teams to seamlessly integrate intelligence into our core data platforms and processes.
Key Accountabilities:
- Data Preparation Management: Extract and integrate moderately complex data from diverse sources. Analyze datasets for potential bias and implement effective mitigation strategies.
- Data Analysis: Conduct exploratory data analysis on complex datasets to uncover trends and patterns that can inform strategic business decisions across different departments.
- Model Development: Implement and deploy artificial intelligence models to address moderately complex business challenges and generate actionable insights. Continuously monitor model performance.
- AI Engineering: Apply robust software and AI engineering principles to design, develop, test, integrate, maintain, and troubleshoot complex generative AI software solutions. Integrate security best practices into all developed and maintained applications.
- Documentation & Reporting: Create clear and comprehensive documentation for development work and code to facilitate support and knowledge sharing within the team.
- Communication: Effectively communicate complex techniques and findings to both technical and non-technical audiences.
- Continuous Learning: Stay abreast of existing and emerging AI and optimization principles, theories, and techniques. Apply this knowledge to deploy AI and optimization models into production, thereby enhancing the organization's analytical capabilities.
- Stakeholder Management: Engage with business stakeholders to understand their needs and collaborate with cross-functional teams to implement AI models for digital applications.
Qualifications: A minimum of 2 years of relevant work experience is required. Typically, individuals with 3 or more years of relevant experience are well-suited for this role.
