Senior Machine Learning Engineer
Tasks
- Architect ML platform
- Build advanced chatbots
- Build embedding pipelines
- Build orchestration layers
- Build production-grade AI agents
- Design multi tenant AI ML infrastructure
- Develop high throughput low latency backends
- Drive model monitoring and observability
- Establish LLMOps evaluation pipelines
- Evaluate build-vs-buy decisions
- Implement CI/CD testing practices
- Implement long term memory architectures
- Implement multi agent state management
- Integrate Model Context Protocol server
- Lead design and security reviews
- Map business requirements to technical designs
- Optimize vector databases
- Own ML production strategy
Perks/Benefits
Skills/Tech-stack
AWS | Agent Framework | Agent systems | Airflow | Argo Workflows | ArgoCD | Autogen | Azure | BigQuery | CI/CD | Cloudflare Workers | Distributed Systems | Docker | ELT | ETL | Embeddings | FastAPI | Fine Tuning | GCP | Guardrailing | JavaScript | Kubernetes | LLMOps | Langchain | Langgraph | MLOps | Model Monitoring | Moderation | Multi-Agent | Multi-Agent Systems | Postgres | PyTorch | Pytest | Python | RAG | React | Scikit-learn | TensorFlow | Terraform | TypeScript | Vector Database | Version control
Education
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