AI Engineer
Summary
Build and deploy AI systems: fine-tune LLMs, implement RAG and agent orchestration, optimize models for edge devices, and set up MLOps pipelines.
- Build context engines
- Build knowledge bases
- Build multi agent planning
- Build recommendation models
- Compress models
- Containerize ML workloads
- Deploy models on edge devices
- Design agent orchestration
- Develop AI guardrails
- Distill knowledge
- Evaluate model quality
- Fine-tune LLMs
- Implement MLOps
- Implement RAG
- Implement agent memory
- Implement function calling
- Implement model serving
- Manage multi domain routing
- Monitor production models
- Optimize on device inference
- Prune models
- Quantize models
- Research LLMs
- Resolve task conflicts