Machine Learning Engineer
Tasks
- Build AI powered data collection systems
- Build observability with monitoring logging tracing and alerting
- Deploy and manage ML and LLM model lifecycle
- Detect model drift and monitor reliability
- Develop LLM based retrieval augmented generation workflows
- Develop distributed event driven cloud native platform components
- Implement evaluation frameworks for extraction and model performance
- Implement prompt orchestration and validation
- Maintain model versioning experiment tracking and model registry
- Support agentic workflows and model tool integrations
Perks/Benefits
Skills/Tech-stack
AWS | Asynchronous processing | Azure | CI/CD | Containerization | Data Pipelines | Distributed Systems | Docker | Embeddings | Experiment tracking | GCP | Kubernetes | LLM Evaluation | MLOps | Machine Learning | Message Queues | Model Monitoring | Prompt engineering | Python | Retrieval-Augmented Generation | SQL | Vector Databases
Education
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