Role overview
Minnesota Sick and Safe Leave accruals of one hour for every 30 worked, up to 48 hours per calendar year unless otherwise provided by law.
The expected salary for this position is $76,000- $129,000. Compensation varies depending on a wide array of factors including but not limited to the specific location, certifications, education, and level of experience. The disclosed range estimate may be adjusted for any applicable geographic differential associated with the location at which the position may be filled. This position is eligible for a discretionary incentive award. The incentive award amount is dependent upon company performance and your personal performance. At Cargill we put people first. As part of your overall rewards, we offer a comprehensive benefit program including medical and/or other benefits dependent on the position offered and hours worked. Visit: https://www.cargill.com/page/my-health/mh-health-and-wellness to learn more (subject to certain collective bargaining agreements for Union positions).
Equal Opportunity Employer, including Disability/Vet.
What we're looking for
- Builds and operates data pipelines supporting training, evaluation, deployment and monitoring of models and AI/ML services on Sgemker.
- Experience working with AI platform components such as LLM gateways, vector databases, retrieval systems or multi-model orchestration.
- Familiarity with retrieval workflows including embedding generation, chunking strategies and scalable retrieval patterns.
- Familiarity with AI observability and evaluation tooling (for example LangSmith or similar platforms) and integrating automated quality checks for AI systems.
- Experience implementing infrastructure-as-code using tools such as Terraform, CDK or similar technologies for managing cloud environments.
- Knowledge of cloud platform fundamentals including networking, identity management, secrets management and secure service communication.
- Experience optimizing performance, reliability and cost efficiency of AI workloads including caching strategies, model routing and workload monitoring.
- Experience using modern developer productivity tools including code assistants and AI-enabled development workflows.