Principal Applied AI Developer, Foundation Models Infrastructure
Tasks
- Architect ML lifecycle platforms
- Build scalable resilient secure ML systems
- Define AI and ML infrastructure strategy
- Design distributed compute workloads
- Develop developer APIs and workflows
- Drive performance scalability cost optimization
- Establish platform reliability observability standards
- Implement CI/CD and automated testing
- Lead cross-team technical initiatives
- Manage infrastructure as code
- Mentor engineers and drive best practices
- Perform root cause analysis
- Support responsible AI deployment
- Translate requirements into technical designs
Perks/Benefits
- Flexible work arrangements
- Health, dental, vision coverage
- Hybrid work arrangement
- Innovation opportunities
- Internal mobility
- Leadership development
- Mentorship
- Professional development
Skills/Tech-stack
API Development | AWS | Amazon SageMaker | Automated testing | CI/CD | Deployment | Distributed Systems | Evaluation | Governance | Inference | Infrastructure as Code | Kubernetes | Model Monitoring | Observability | Ray | SLAs | SLO | System design | Training | Versioning | “as-code”
Education
N/A
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