Machine Learning Engineer
Tasks
- Build and maintain ML/AI systems for production
- Collaborate cross-functionally with data scientists, engineers, and product teams
- Contribute to architecture decision records and system upgrades
- Develop APIs and integration layers for ML solutions
- Ensure operational excellence for availability and latency
- Establish monitoring and reliability mechanisms
- Implement CI/CD, testing, and release strategies for ML
- Scale AI agentic systems and manage complex ML lifecycles
- Translate infrastructure issues into business risks
Perks/Benefits
Skills/Tech-stack
AWS | Airflow | Alerting | Data Engineering | Databricks | FastAPI | Feature serving | GRPC | Graph Database | Kubernetes | Langchain | Llamaindex | ML deployment | ML orchestration | Model Quantization | Monitoring | NumPy | Pandas | Prefect | PyTorch | Python | Regression Detection | Request batching | Retrieval-Augmented Generation | SQL | Scikit-learn | Spark | TensorFlow | Workflow Orchestration
Regions
Countries
States
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