AI Engineer
Tasks
- Automate builds with CI CD pipelines
- Build Retrieval Augmented Generation systems
- Build agent workflows with AutoGen
- Build agent workflows with LangChain
- Build agent workflows with LangGraph
- Deploy local vector databases
- Evaluate model weights from Hugging Face
- Fine tune models with LoRA
- Fine tune models with PEFT
- Implement agent memory loops
- Implement local data governance controls
- Monitor system metrics with OpenTelemetry
- Optimize model size with Quantization
- Orchestrate clusters with Kubernetes
- Package models with Docker
- Serve models with Ollama
- Serve models with TGI
- Serve models with Triton Inference Server
- Serve models with vLLM
- Set up air gapped model deployment
- Set up private logging and guardrails
- Use Grafana dashboards
- Use Prometheus for monitoring
Perks/Benefits
- N/A
Skills/Tech-stack
AWQ | Access Control | Air Gapped Computing | Air-gapped | Autogen | C plus plus | CI/CD | Data Governance | Docker | GPTQ | Gguf | GitLab CI | Grafana | Hugging Face | Inference Server | Java | Jenkins | Kubernetes | Langchain | Langgraph | LoRA | Milvus | NVIDIA CUDA | Nemo Guardrails | Ollama | OpenTelemetry | PEFT | PGVector | Pinecone | Prometheus | Python | Qdrant | Quantization | RAG | ROCm | Retrieval-Augmented Generation | Rust | TGI | Triton Inference | Triton Inference Server | VGPU | VLLM | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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