AI Principal Engineer, VP
Tasks
- Build embedding pipelines and RAG systems
- Collaborate with feature teams to deliver high-quality software
- Create architecture models and roadmaps
- Define and govern engineering and design solutions
- Deploy models with MLOps and CI CD
- Design and engineer complex software, scripts, and tools
- Design and engineer software with customer outcomes
- Determine design and delivery approach
- Develop and optimize LLM pipelines
- Drive end to end automation and simplification
- Ensure observability security and performance tuning
- Implement supervised and unsupervised learning
- Improve software delivery with platform standards
- Orchestrate LLM workflows with prompt engineering
- Perform time series forecasting
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS | Agile | Anthropic | Automation | Automl | Bug tracking | CI/CD | Data Processing | Data Processing Pipelines | DevOps | Embeddings | Experiment tracking | Feature Engineering | Feature Stores | Fine Tuning | GCP | GPU Computing | LLM | LLM orchestration | MLOps | Machine Learning | Model Deployment | Model Evaluation | Observability | OpenAI | Performance Tuning | Processing pipelines | Prompt engineering | Python | RAG | Resilience | Scalability | Security | Series forecasting | Time Series | Time Series Forecasting | Version control | Virtualization
Education
N/A
Roles
AI | AI Principal | AI Principal Engineer | Engineer | Principal | Principal Engineer
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