AI Principal Engineer, VP
Tasks
- Build LLM and ML data pipelines
- Collaborate with feature teams to deliver software
- Create engineering roadmaps
- Define scripting tools for platform delivery
- Design software architectures
- Develop supervised and unsupervised learning systems
- Enable end-to-end automation
- Ensure observability and performance tuning
- Evaluate and integrate LLM capabilities
- Implement ML Ops standards
- Improve resilience security performance scalability
- Integrate model APIs
- Manage experiment tracking and model deployment
- Orchestrate LLM workflows
- Provide engineering governance
- Set up CI/CD pipelines
Perks/Benefits
- N/A
Skills/Tech-stack
API Integration | Agile | Architecture Design | Automl | CI/CD | Data Processing | Data Processing Pipelines | Deep learning | DevOps | Embeddings | Experiment tracking | Feature Engineering | Feature Store | GPU Computing | LLM Pipelines | LLM orchestration | MLOps | Machine Learning | Model Deployment | Model Evaluation | Observability | Optimization | Performance Tuning | Processing pipelines | Prompt engineering | Python | Retrieval-Augmented Generation | Scalability | Security | Series forecasting | Supervised Learning | Time Series | Time Series Forecasting | Unsupervised Learning | Virtualization
Education
N/A
Roles
AI | AI Engineer | Engineer | Principal | Principal Engineer
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