AI Developer
Core
Design, train, optimize, and deploy LLM models in on-prem and offline environments to build end-to-end LLM pipelines.
Role type
Senior IC machine-learning engineer (LLM & RAG)
Builds
Production LLM pipelines, RAG systems, and offline inference frameworks
Domain
Artificial Intelligence / Machine Learning / Enterprise Software
Deliverable
production ML models
Required skills
Python, PyTorch, supervised fine-tuning (SFT), LoRA/Q-LoRA, Hugging Face Transformers, RAG pipeline design, vector stores (FAISS/Chroma/pgvector), MCP integration, model quantization (GGUF/GPTQ/AWQ), GPU optimization (CUDA), Docker, Git, Azure DevOps
Preferred skills
agentic workflows, HyDE/re-ranking, ML model registries, AWS hybrid deployments, enterprise compliance
Technologies
LLaMA, Mistral, Qwen, vLLM, TGI, Ollama, Postgres, MySQL, XML/XSD, python-docx, OpenXML
Responsibilities
Train and fine-tune LLMs using SFT and LoRA pipelines; Design and implement end-to-end RAG pipelines with hybrid search and re-ranking; Deploy and maintain models in air-gapped environments using quantization and local inference frameworks; Build backend services and CI/CD pipelines for offline ML workflows; Integrate MCP servers to connect LLMs with external tools and APIs.
Seniority
Senior, hands-on IC
