Senior ML Ops Engineer
Tasks
- Build LLM observability frameworks
- Build model serving pipelines
- Build prompt platform tooling
- Configure Provisioned Throughput
- Develop LLM evaluation tooling
- Drive security review for AI vendors
- Ensure stability of LLM calls
- Host fine tuned machine learning models
- Host open weight machine learning models
- Implement agentic evaluations
- Improve data annotation tooling
- Maintain LLM observability tools
- Maintain backups
- Manage LLM rate limits
- Optimize LLM costs with caching and batching
Perks/Benefits
Skills/Tech-stack
AWS | Batching | Caching | Data Annotation | Distributed Systems | Evaluation | Kubernetes | LLM | Machine Learning | Model Serving | Observability | Prompt engineering | Python | Rate Limiting | Terraform | Training pipelines
Education
N/A
Regions
Countries
States
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