The AI Engineer will design AI solutions for data management and governance, utilizing ML and automation to enhance data quality and compliance. Responsibilities include data preparation, model development, stakeholder management, and continuous learning within AI principles.
Job Purpose and Impact
The AI Engineer will design and build AI-enabled solutions that enhance Data Management and Data Governance capabilities across Cargill. In this role, you will apply machine learning, generative AI, and automation to improve data quality, metadata management, master data, data classification, lineage, and governance workflows-helping ensure data is trusted, compliant, and business-ready. You will collaborate closely with Data Engineering, Data Domain & Governance, Architecture, Security, and Business/Function teams to embed intelligence into core data platforms and processes.
Key Accountabilities
Qualifications
Minimum requirement of 2 years of relevant work experience. Typically reflects 3 years or more of relevant experience.
The AI Engineer will design and build AI-enabled solutions that enhance Data Management and Data Governance capabilities across Cargill. In this role, you will apply machine learning, generative AI, and automation to improve data quality, metadata management, master data, data classification, lineage, and governance workflows-helping ensure data is trusted, compliant, and business-ready. You will collaborate closely with Data Engineering, Data Domain & Governance, Architecture, Security, and Business/Function teams to embed intelligence into core data platforms and processes.
Key Accountabilities
- DATA PREPARATION MANAGEMENT: Conducts extraction and integration of moderately complex data from different data sources, analyses the ways in which datasets may be biased and applies mitigation strategies.
- DATA ANALYSIS: Reviews moderately complex data sets for exploratory data analysis to identify trends and patterns that inform business strategies across various areas.
- MODEL DEVELOPMENT: Implements and deploys artificial intelligence models, including review of ongoing performance to solve moderately complex business problems and derive actionable insights.
- AI ENGINEERING: Applies software and artificial intelligence engineering patterns and principles to design, develop, test, integrate, maintain and troubleshoot complex and varied generative artificial intelligence software solutions and incorporates security practices in newly developed and maintained applications. .
- DOCUMENT & REPORTING: Collaborates documenting development and code in ways that allow for support and knowledge sharing.
- COMMUNICATION: Communicates techniques and results to technical and non-technical audiences.
- CONTINUOUS LEARNING: Supports examination of existing and emerging artificial intelligence and optimization principles, theories, and techniques to deploy artificial intelligence and optimization models into production, improving the organization's analytical capabilities.
- STAKEHOLDER MANAGEMENT: Works closely with businesses to understand needs, and supports collaboration with cross functional teams to implement artificial intelligence models for digital applications.
Qualifications
Minimum requirement of 2 years of relevant work experience. Typically reflects 3 years or more of relevant experience.
Similar Jobs
Automotive
Lead end-to-end ML projects for manufacturing: collaborate with stakeholders, design and deploy ML models (classification, regression, clustering, recommendation), implement MLOps/CI-CD, monitor models in production, ensure data security and compliance, perform EDA/feature engineering/ETL, and document outcomes.
Top Skills:
Azure MlKubeflowMlflowNoSQLPythonPyTorchScikit-LearnSQLTensorFlowVertex AiXgboost
The Senior Machine Learning Engineer will develop machine learning models, particularly focusing on Generative AI solutions and Agentic AI architectures, while collaborating with teams to optimize existing models and systems.
Top Skills:
AWSAzureGCPKubeflowPythonPyTorchSagemakerScikit-LearnSQLTensorFlow
As a Staff Machine Learning Engineer, you'll lead the development of scalable AI/ML systems, mentor engineers, and drive innovation while collaborating across teams to deliver technical solutions.
Top Skills:
AWSAzureGCPGoKubeflowPythonPyTorchRustSagemakerScikit-LearnSQLTensorFlow
What you need to know about the Bengaluru Tech Scene
Dubbed the "Silicon Valley of India," Bengaluru has emerged as the nation's leading hub for information technology and a go-to destination for startups. Home to tech giants like ISRO, Infosys, Wipro and HAL, the city attracts and cultivates a rich pool of tech talent, supported by numerous educational and research institutions including the Indian Institute of Science, Bangalore Institute of Technology, and the International Institute of Information Technology.
