Manager, Platform Engineering, AI & Data Science
Manager, Platform Engineering, AI & Data Science
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Salary Not Disclosed
1 Vacancy
Job Description
Cargills size and scale allows us to make a positive impact in the world. Our purpose is to nourish the world in a safe responsible and sustainable are a family company providing food ingredients agricultural solutions and industrial products that are vital for living. We connect farmers with markets so they can prosper. We connect customers with ingredients so they can make meals people love. And we connect families with daily essentials from eggs to edible oils salt to skincare feed to alternative fuel. Our 160000 colleagues operating in 70 countries make essential products that touch billions of lives each day. Join us and reach your higher purpose at Cargill.
Job Purpose and Impact
The Manager for AI Platform Engineering leads the team that designs builds and operates Cargills enterprise AI-Ops platformcovering MLOps LLMOps/GenAIOps HPC scheduling and optimisation services (e.g. Gurobi RStudio Workbench). You will own the platform roadmap allocate people and budget drive project delivery and embed best-in-class reliability security and compliance practices. Success is measured by platform uptime model-to-production velocity cost-to-serve trends and team engagement.
Key Accountabilities
Platform Ownership & Road-mapping
- Define and maintain the technical roadmap for MLOps LLMOps HPC and optimization tooling
- Oversee the portfolio of AI-Ops projects; align scope schedule and budget to business objectives.
Technical Guidance & Governance
- Champion infrastructure-as-code GitOps and CI/CD pipelines
Quality Reliability & Compliance
- Set and monitor SLIs/SLOs for training inference and optimization services; lead post-incident reviews.
- Ensure Responsible-AI guardrails data-privacy and license-management policies are implemented.
Process Improvement & Automation
- Drive continuous-improvement initiatives (test-driven development auto-scaling policies cost dashboards).
Stakeholder & Customer Engagement
- Partner with product managers data-science leads and security/compliance teams to capture requirements and set priorities.
Team Management & Talent Development
- Set performance objectives conduct regular feedback and coaching sessions and create growth plans.
- Foster an inclusive culture that values experimentation blameless post-mortems and knowledge sharing
Qualifications
- Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.
Preferred:
- 3 years running production MLOps/LLMOps or HPC environments
- 2 years managing engineers or cross-functional delivery teams
Equal Opportunity Employer including Disability/Vet.
Required Experience:
Manager
Employment Type
Full-Time
