Staff Machine Learning Ops Engineer
Tasks
- Build CI/CD pipelines for ML
- Build vector retrieval infrastructure
- Create LLM Gateway and model serving
- Define ML platform vision and roadmap
- Design cloud native distributed training and inference
- Design platform abstractions and tooling
- Develop GenAI and LLM platform capabilities
- Establish ML observability standards
- Identify and eliminate research to production bottlenecks
- Implement drift and data quality monitoring
- Lead ML lifecycle architecture
- Mentor engineers and raise technical standards
Perks/Benefits
Skills/Tech-stack
AWS | Alerting | CI/CD | Data Lineage | Distributed Training | Docker | Drift Detection | GCP | Generative AI | Infrastructure as Code | Kubernetes | LLM-Ops | Langchain | Language Models | Large Language Models | Llamaindex | MLOps | Machine Learning | Model Deployment | Model retraining | Monitoring | Observability | Prompt evaluation | Python | Retrieval-Augmented Generation | Terraform | Vector Databases | Vector Search | “as-code”
Education
N/A
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