Senior Machine Learning Engineer
Tasks
- Build RAG-based applications
- Build end-to-end ML pipelines
- Deploy to AWS
- Design ML models
- Design event-driven pipelines
- Design scalable microservices architectures
- Detect data drift
- Detect model drift
- Develop inference services
- Engineer features
- Ensure observability
- Evaluate model metrics
- Implement CI/CD pipelines
- Manage LLM context
- Monitor model performance
- Optimize prompts
- Trigger retraining pipelines
- Tune hyperparameters
Perks/Benefits
Skills/Tech-stack
AWS | AWS Lambda | AWS S3 | Amazon EKS | CI/CD | CloudFormation | Data Drift | Docker | Event Driven | Event-driven architecture | FastAPI | Feature Engineering | Flask | Hyperparameter Tuning | LLM | Language Processing | Machine Learning | Microservices | Model Drift | Model Evaluation | Monitoring | Natural Language | Natural Language Processing | Observability | PostgreSQL | Prompt engineering | Python | REST API | Retrieval-Augmented Generation | SQL | Terraform | Time Series | Vector Databases
Education
N/A
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