Lead Data/AI Engineering - Applied AI
Tasks
- Apply continuous integration and continuous delivery
- Architect machine learning solutions
- Build data pipelines and analytical data models
- Build generative AI and large language model workflows
- Build scalable decision support solutions
- Create evaluation standards for AI models
- Deploy and monitor machine learning and AI services
- Develop forecasting and anomaly detection models
- Develop semantic models and governed data products
- Ensure security and lifecycle management for AI systems
- Implement data contracts and data quality controls
- Implement retrieval-augmented generation
- Lead mentoring and technical guidance for engineers
- Set up model monitoring and data drift detection
Perks/Benefits
- 401k plan
- Adoption reimbursement
- Disability benefits
- Employee assistance program
- Employee discounts
- Employee wellness programs
- Life and accidental death insurance
- Long-term disability
- Medical, dental & vision coverage
- Paid caregiver leave
- Paid parental leave
- Paid time off
- Short-term disability
- Tuition reimbursement
Skills/Tech-stack
APIs | Agent workflows | Azure | Azure Machine Learning | Azure OpenAI | Continuous Delivery | Continuous integration | Data Drift | Data Drift Detection | Databricks | Docker | Drift Detection | FastAPI | MLflow | Machine Learning | Model Monitoring | Observability | Python | Retrieval-Augmented Generation | SQL | Security | Semantic Search | Snowflake | Statistical modeling | Tool integration | Vector Search | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Data Engineer | Data Scientist | Engineer | Learning Engineer | Machine Learning Engineer | Scientist
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