ai engineer (prediction model).

• AI & LLM Proficiency: A solid understanding of Machine Learning and Deep Learning. You should have hands-on experience using PyTorch, Hugging Face, and working with LLM APIs.
• Advanced AI Techniques: Experience or academic projects involving
• Retrieval-Augmented Generation (RAG), AI Agents, or multimodal systems (working with text, voice, or images).
• Backend & Systems Programming: A strong foundation in Python is essential.
• Familiarity with FastAPI to build AI-powered services is a major plus.
• DevOps Fundamentals: You should know how to use Git for version control and have a basic understanding of Docker for containerization.

Key Responsibilities

• AI Strategy Support: Help contribute to our 3-year roadmap as we move toward autonomous, self-adjusting factory operations.
• Data Connections: Help design automated pipelines using SQL Server to connect factory machines and sensors into our central AI system.
• Building RAG Systems: Assist in designing and deploying RAG pipelines for our internal AI chatbots to ensure they provide accurate information.
• MLOps & Deployment: Work on the full lifecycle of AI models—from development to the factory floor—ensuring they stay accurate and secure.
• Collaboration: Work closely with senior engineers and help explain AI results to management and international stakeholders.

Nice to Haves

• Performance Tuning: Any exposure to C++, Rust, or CUDA.
• Hardware Knowledge: A basic understanding of how CPUs, GPUs, and SSDs work together.
• Frontend Skills: Experience building simple user interfaces with React or Next.js.