MLOps & AI Platform Engineer
Tasks
- Build observability for ML and GenAI systems
- Deploy and optimize LLM inference services
- Deploy containerized workloads on Kubernetes
- Design and maintain ML lifecycle infrastructure
- Engineer ML and AI platforms
- Ensure security, reliability, and compliance
- Evaluate and integrate MLOps and GenAI frameworks
- Implement CI/CD pipelines
- Manage GPU clusters and inference optimization
- Standardize ML workflows and model packaging
- Track and manage machine learning models with MLflow
Perks/Benefits
- N/A
Skills/Tech-stack
Azure Databricks | Azure DevOps | Batching | CI/CD | Caching | Compliance | Data Engineering | Data Security | Distributed Computing | Docker | GPU Management | GitHub Actions | Governance | Inference Optimization | Jenkins | Kubernetes | Language Models | Large Language Models | Logging | MLflow | Model Quantization | Monitoring | Observability | Python | Tracing | Vector Databases
Education
N/A
Roles
AI | AI Platform Engineer | Engineer | MLOps Engineer | Platform Engineer
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