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# AI/ Machine Learning Engineer - (ATL or MSP)

- **Company:** Cargill
- **Location:** Atlanta, GA, United States
- **Experience:** Experienced
- **Salary:** $76,000.0 - $129,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Application Release Automation, Automated Storage and Retrieval Systems, Automation of Tests, Code Review, Continuous Integration, Information Leak Prevention, Identity and Access Management, Key Management, Machine Learning, Productivity Software, Azure Machine Learning, Runbook, Management of Software Versions, Data Logging, Cloud Platform System, Large Language Models, Caching, AI Platforms, Terraform, Data Pipelines, Api Management
- **Published:** June 21, 2026
- **Apply:** https://www.juju.com/job/00000000g9xufa

## About the Role

+ Minimum requirement of 2 years of relevant work experience. Typically reflects 3 years or more of relevant experience.

Preferred Experience:

 + 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.

## Description

+ **CI/CD & RELEASE AUTOMATION:** Implements CI/CD pipelines including automated testing, evaluation checks, contract testing and controlled environment promotion to ensure reliable, repeatable and production-ready AI/ML platform and model deployments.

 + **PLATFORM COLLABORATION & GOVERNANCE:** Contributes to shared platform standards including API contracts, semantic versioning, repository contribution models, documentation and code reviews to enable multiple engineering teams to safely build and operate services on the platform.

 + **OBSERVABILITY & OPERATIONS:** Applies telemetry-first engineering practices including logs, metrics and traces to support monitoring, reliability and operational excellence. Contributes to runbooks, incident response, operational readiness and postmortems.

 + **SECURITY & RESPONSIBLE AI:** Implements secure-by-default practices including secrets management, least privilege access, safe logging and protections against prompt injection, tool misuse and data leakage when building and operating AI services.


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