Applied AI/ML Software Engineer-Supply Chain AI and Decision Intelligence
Tasks
- Build automated MLOps and LLMops pipelines for current data
- Create guardrail frameworks for toxicity hallucination and latency
- Deploy applied AI models into supply chain Google Cloud environment
- Design decision intelligence frameworks for risk identification and mitigation
- Design pipelines connecting knowledge graph updates to model inference engines
- Design reusable integration patterns and data contracts for scaling across business units
- Establish AI driven SDLC with automated testing
- Gather business requirements and translate into technical specifications
- Implement agentic workflows and AI assisted coding
- Integrate models with enterprise knowledge graphs
- Simulate what if scenarios using generative AI and graph analytics
Perks/Benefits
- Employee resource groups
- Flexible family care days
- Medical, dental & vision coverage
- Option to purchase additional vacation time
- Paid Holidays
- Paid parental leave
- Paid time off
- Prescription Drug Coverage
- Relocation assistance
- Subsidized back-up childcare
- Tuition assistance
- Vehicle discount program
Skills/Tech-stack
AI Platform | AWS SageMaker | Agentic Workflows | Automated testing | Azure ML | COTS Integration | Cloud Computing | Cloud platform | Cypher | GCP AI | GCP AI Platform | Generative AI | GitHub Copilot | GitHub pull requests | Google Cloud | Google Cloud Platform | Graph analytics | Knowledge graphs | Kubeflow | LLM safety | LLMOps | Latency optimization | MLOps | MLflow | Machine Learning | Observability | Prompt engineering | Pull Requests | Python | RAG | SQL | Vertex AI
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