AI/ML Consultant – LLM Deployment

Remote Full-time
to set up and configure a self-hosted large language model (Llama 3.1) on our Linux server infrastructure for automated report generation. Primary Objective: Deploy and configure Llama 3.1 (or equivalent) 8B on our hosted Linux server (CPU-only) and create an API service that our SafetyNet Platform can call for AI-powered report generation. Specific Deliverables: Server Environment Setup Configure Linux (Ubuntu 22.04) server environment Install Python 3.11, dependencies, and required libraries Set up virtual environment and security configurations AI Model Installation & Configuration Download and install Llama 3.1 8B Instruct model Optimize model configuration for CPU-only inference Implement quantization if needed for performance Test model functionality and response quality API Service Development (Nice to have) Create REST API service (Flask/FastAPI) for report generation Implement secure endpoints for our SafetyNet Platform to call Add error handling, logging, and health check endpoints Configure service to auto-start on server reboot (systemd) Security & Performance Configure firewall rules (allow only our application server) Implement authentication/API key system Optimize for 30-60 second response times Set up monitoring and logging Documentation & Training Comprehensive setup documentation API usage guide with examples Troubleshooting guide 2-hour knowledge transfer session with our development team Testing & Validation Generate 10+ test reports with sample data Validate output quality and format Performance testing under load Integration testing with our platform (we'll provide API endpoints) Technical Requirements Must Have: 3+ years experience with Python and machine learning frameworks (PyTorch, Transformers) Experience deploying and running large language models (Llama, GPT, Mistral, etc.) Strong Linux system administration skills (Ubuntu/Debian) Experience with API development (Flask, FastAPI, or similar) Understanding of CPU-based ML inference and optimization Experience with Hugging Face model hub Knowledge of systemd service configuration Security best practices for production systems Nice to Have: Experience with model quantization and optimization (bitsandbytes, ONNX) DevOps experience (Docker, monitoring tools) Previous work with government or healthcare systems (HIPAA/FERPA compliance) Experience with justice system or social services applications Apply tot his job
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