AI/ML Implementation Engineer
Tasks
- Apply prompt engineering for LLMs
- Automate quality workflows
- Collaborate with data engineers and data scientists
- Define data requirements and solution architecture
- Define scalable AI deployment approach
- Deliver preventive quality AI solutions
- Design develop deploy AI and ML applications
- Document solution designs and model performance
- Enable predictive quality insights
- Ensure AI solutions are secure and scalable
- Gather requirements from stakeholders
- Lead AI adoption analysis
- Lead cross-functional project execution
- Perform model validation and robustness updates
- Prioritize AI use cases
- Propose responsible AI improvements
- Reduce quality related incidents
Perks/Benefits
- 401k matching
- Dental insurance
- Disability benefits
- Employee assistance program
- Health coaching
- Life insurance
- Medical insurance
- Paid parental leave
- Prescription Drug Coverage
- Relocation assistance
- Remote work
- Tuition assistance
- Vision insurance
Skills/Tech-stack
8D | APQP | AWS | AWS Lambda | Amazon Bedrock | Amazon S3 | Amazon SageMaker | Artificial Intelligence | Bias Mitigation | Chain-of-Thought | Data Engineering | Data Modeling | Deployment | Experiment tracking | FMEA | FastAPI | Few-Shot Learning | Few-shot | Git | Language Models | Large Language Models | MLOps | Machine Learning | Model Security | Model Validation | Model versioning | Production Machine Learning | Prompt engineering | Python | Quality management | Responsible AI | Semantic data | Semantic data modeling | Zero-Shot | Zero-shot Learning
Education
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