AI Engineer
Tasks
- Benchmark GPU compute requirements
- Build agent workflows with AutoGen
- Build agent workflows with LangChain
- Build agent workflows with LangGraph
- Build air gapped deployment workflows
- Build retrieval-augmented generation pipelines
- Deploy LLMs with Ollama
- Deploy LLMs with vLLM
- Deploy models with TGI
- Deploy models with Triton Inference Server
- Deploy vector databases locally
- Fine tune models with LoRA
- Implement local data governance
- Manage agent memory loops locally
- Optimize model memory with quantization
- Orchestrate clusters with Kubernetes
- Package models with Docker
- Select model weights from Hugging Face
- Set up private logging and guardrails
Perks/Benefits
- N/A
Skills/Tech-stack
AWQ | Autogen | C++ | CUDA | Docker | GPTQ | Gguf | GitLab CI | Grafana | Hugging Face | Inference Server | Jenkins | Kubernetes | Langchain | Langgraph | LoRA | Milvus | Ollama | OpenTelemetry | PEFT | PGVector | Pinecone | Prometheus | Python | Qdrant | RAG | ROCm | Retrieval-Augmented Generation | Rust | TGI | Triton Inference | Triton Inference Server | VGPU | VLLM
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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