Applied AI Engineer II
Tasks
- Build scalable data pipelines
- Build tools for model deployment monitoring observability
- Deploy production grade machine learning systems
- Develop model training workflows
- Develop on premises MLOps solutions
- Improve CI/CD pipelines for machine learning
- Optimize infrastructure using Linux Docker Kubernetes
- Optimize machine learning models for performance throughput scalability
- Perform code reviews and testing
- Troubleshoot full machine learning stack
Perks/Benefits
- Accidental insurance
- Education reimbursement
- Employee referral program
- Flexible time off
- Flexible working hours
- Learning and development support
- Life insurance
- Medical insurance
- Parental leave
- Remote-first
- Tech stipend
- Vacation leave
- Work from home stipend
Skills/Tech-stack
AWS | CI/CD | CUDA | Data Pipelines | Docker | Google Cloud | Kubernetes | Linux | MLOps | Machine Learning | Microsoft Azure | Model Deployment | Model Monitoring | Observability | Python | Software testing
Education
N/A
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