AI Engineer at ShyftLabs

📋 Description

• Design and implement ML/LLM systems
• Optimize inference performance and cost
• Fine-tune foundation models for use cases
• Implement prompt engineering strategies
• Build backend infrastructure for AI apps
• Implement and maintain MLOps pipelines

🎯 Requirements

• 4–8 years in LLMs, backend eng, and MLOps
• LLM expertise
• Model fine-tuning: LoRA/QLoRA/adapters
• Inference optimization: quantization, pruning, caching
• Prompt engineering: few-shot, chain-of-thought, RAG
• Backend engineering: Python with FastAPI/Flask; REST APIs

🎁 Benefits

• Insurance package
• Learning and development resources