Senior AI Data Science Engineer

At Cargill, our vast resources enable us to make a meaningful difference in the world. Our mission is to nourish the globe in a safe, responsible, and sustainable manner. As a family company, we provide essential food, ingredients, agricultural solutions, and industrial products that enhance lives globally. We connect farmers to markets, customers to ingredients, and families to daily necessities—ranging from eggs to skincare, and feed to alternative fuel. With 160,000 colleagues in 70 countries, we produce vital products that impact billions of lives daily. Join us to fulfill your higher purpose at Cargill.

Job Purpose and Impact

• As a leader in AI and Data Science, you will provide prominent thought leadership in creating and implementing innovative artificial intelligence solutions that significantly enhance strategic decision-making. You will collaborate with various teams to develop and execute the organization's AI strategy, guiding the implementation of relevant platforms and products to maximize business value while fostering a culture of compliance within our governance framework. Your role will also involve identifying opportunities for process improvements and leading initiatives to ensure high-quality outcomes and measurable business impact.

Key Accountabilities

• Technical Strategy & Architecture:
  • Define a comprehensive multi-year AI Operations roadmap that includes model experimentation, high-performance computing (HPC) scheduling, inference serving, and data lineage.
  • Assess and integrate the most suitable open-source and commercial tools.
• Platform Engineering & Operations:
  • Develop and maintain continuous integration/continuous deployment (CI/CD) pipelines for model training involving GPU/CPU, feature engineering, and automated testing across cloud environments and HPC clusters.
  • Implement scalable vector databases and caching systems to support low-latency Generative AI workloads.
  • Optimize scheduler policies for maximum efficiency and cost-effectiveness.
  • Monitor system performance, address escalations, and lead post-incident evaluations.
• Governance & Compliance:
  • Advocate for data privacy, model risk management, and export control compliance; ensure policy checks are embedded within all pipelines.
  • Provide thorough audit-ready documentation for SOC-2, ISO 27001, and relevant regulations (such as food safety and trade compliance).
• Leadership & Mentoring:
  • Guide senior engineers and data scientists in scalable MLOps and HPC patterns.
  • Facilitate AI platform design reviews and contribute to internal communities of practice.

Qualifications

• Minimum requirement: 6 years of relevant experience.
• Typical requirement: 10+ years in software or data engineering, with a minimum of 4 years of experience managing production ML or HPC workloads, and 2+ years in Generative AI or Large Language Model Operations. Leadership experience overseeing cross-functional engineering teams is preferred.

Equal Opportunity Employer, including Disability/Vet.