Principal AI Engineer
Tasks
- Build backend services and APIs for model capabilities
- Build data and feature pipelines from on chain and warehouse data
- Contribute to AI infrastructure and model serving platform
- Define architecture and engineering standards
- Deploy real time and batch AI services
- Design and build production AI systems
- Ensure data quality lineage and operational robustness
- Evaluate model behavior and decision quality
- Improve observability autoscaling reliability and deployment patterns
- Monitor service performance reliability and maintainability
- Translate business priorities into technical systems
Perks/Benefits
- 401k
- Commuter benefits
- Continuing education reimbursement
- Dental insurance
- Health insurance
- Paid family leave
- Paid time off
- Vision insurance
Skills/Tech-stack
AWS | Application Programming | Application Programming Interfaces | Autoscaling | Azure | Batch Processing | CI/CD | Cloud Computing | Containerization | Data Modeling | Data Pipelines | Deep learning | Docker | Feature Engineering | GCP | Generative AI | GitHub Actions | Infrastructure as Code | Kubernetes | Language Models | Large Language Models | Machine Learning | Model Evaluation | Model Serving | Monitoring | Observability | Optimization | Programming interfaces | Python | Ray | Real Time | Real-time Processing | Reliability Engineering | SQL | Spark | Terraform | Time processing | Token Caching | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer | Principal | Principal AI Engineer
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