AI / ML Engineer
Tasks
- Architect and build large-scale AI systems
- Build agent architectures
- Collaborate with cross-functional teams
- Design data models and APIs
- Design workflow-oriented AI systems
- Develop real-time analytics systems
- Diagnose and resolve performance issues
- Implement and maintain ML platforms
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Agent Frameworks | Agent systems | Anthropic SDK | Autoscaling | Bedrock | CI/CD | Cloud Native | Cloud-native inference | Containerization | Data Architectures | Event Driven | Event-driven architecture | Feature Stores | GPU Workloads | Graph-based | Graph-based execution | Inference services | Kubeflow | Langgraph | ML pipelines | MLflow | Multi-Agent | Multi-Agent Systems | OpenAI SDK | PyTorch Lightning | Pydantic AI | Python | RAG Pipelines | Real Time | Real-time analytics | Retries | Scikit-learn | State management | Streaming systems | Time Series | Time-series systems | Vector Databases | Workflow Orchestration
Education
Regions
Countries
States
Cities
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