Principal ML Engineer
Tasks
- Build self service ML model deployment pipelines
- Collaborate with data scientists and engineers to operationalize ML solutions
- Create RESTful APIs for model lifecycle management
- Create cloud native ML workflows
- Design and maintain deployment infrastructure
- Design machine learning platforms and pipelines
- Develop model lifecycle infrastructure
- Develop tools for model development deployment monitoring reporting
- Implement CI CD pipelines and automated ML workflows
- Monitor and manage ML model deployments
- Provide technical guidance and mentor junior team members
Perks/Benefits
- Accidental coverage
- Employee assistance program
- Employee well-being
- Flexible paid time off
- Hybrid work model
- Mediclaim
- Paid Holidays
- Parental leave
- Provident fund
- Sick leave
- Term life insurance
- Training
Skills/Tech-stack
AWS | CI/CD | Celery | Data Pipelines | Django | Docker | EC2 | FastAPI | Flask | Grafana | Jenkins | Keras | Kubernetes | Linux | ML SDLC | Machine Learning | Microservices | MongoDB | PostgreSQL | PyTorch | Python | RESTful API | S3 | Scikit-learn | Splunk | Terraform
Education
N/A
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