ML Ops Engineer - Reading
3 days ago

Job summary
Design multi-agent architectures: define agent roles (planner, researcher, retriever, executor, reviewer), toolboxes, handoffs, memory strategy (short/long-term), and supervisor policies for safe collaboration.- Build high-quality RAG: implement ingestion, chunking, embeddings, indexing, and retrieval with evaluation (precision/recall , groundedness , hallucination checks) , guardrails , and citations.
- Productionize on AWS: leverage services like Bedrock (Agents/Knowledge Bases/Flows) Lambda API Gateway S3 DynamoDB OpenSearch Vector DB Step Functions and CloudWatch for tracing and alerts.
- MLOps LLMOps : automate CI CD GitOps containerization Docker Kubernetes infra-as-code secrets IAM blue green rollbacks and data feature pipelines.
Job description
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