Senior Machine Learning Engineer
Tasks
- Build agent runtime and registry
- Build agentic applications and internal automation
- Build and operate deployment platform for AI tools
- Build retrieval and knowledge access over internal systems
- Collaborate with InfoSec data scientists and business to define requirements
- Create governed data access layer
- Design build deploy and operate internal AI platform
- Develop ML and agent microservices lifecycle
- Implement CI CD with security checks
- Implement risk tiered deployments
- Implement security and change management thinking
- Monitor latency errors and alerts in production
- Own existing codebases and workflows
- Plan design implement deploy and monitor ML services
- Set up monitoring and rollback for deployments
- Write clean efficient reusable maintainable code
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agent Orchestration | CI/CD | Datadog | Docker | Embeddings | FastAPI | Flask | GCP | Grafana | HTTP Chunked | HTTP chunked transfer | Kafka | LLM | Langgraph | Llamaindex | Message Queues | Model Context Protocol | Monitoring | Observability | PGVector | Pinecone | Prompt engineering | Python | RAG | REST APIs | RabbitMQ | Retrieval | SQL | SQS | Server-Sent Events | Tool-Calling | Vector Databases | Weaviate | WebSockets
Education
N/A
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