AI/ML Implementation Engineer
Tasks
- Analyze AI adoption maturity in quality processes
- Apply prompt engineering for LLM quality tools
- Automate quality workflows with predictive insights
- Collaborate with data engineers data scientists and AI ML engineers
- Define data requirements and solution architecture
- Define homologation approach for scalable AI deployment
- Deliver preventive quality AI ML quick wins
- Design develop deploy production AI ML applications
- Document solution designs model performance and data definitions
- Ensure AI solutions are robust secure scalable production ready
- Gather quality data needs from business stakeholders
- Lead cross-functional project execution
- Prioritize AI use cases for quality suite roadmap
- Propose responsible AI approaches to improve quality solutions
Perks/Benefits
- 12 paid holidays
- Adoption Assistance
- Disability benefits
- Employee assistance program
- Health Coach
- Life insurance
- Medical, dental & vision coverage
- Paid parental leave
- Permissive time off
- Prescription Drug Coverage
- Relocation assistance
- Retirement savings plan
- Tuition assistance
Skills/Tech-stack
8D | APQP | AWS | Bedrock | Bias Mitigation | Chain-of-Thought | Data Modeling | Data models | Deployment | Experiment tracking | FMEA | FastAPI | Few-shot | Git | Lambda | Language Models | Large Language Models | MLOps | Model Validation | Model versioning | Prompt engineering | Python | Responsible AI | S3 | SAP | SageMaker | Salesforce | Security | Semantic data | Semantic data models | Zero-Shot
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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