We provide dedicated AI/ML engineers who design, build, and deploy AI solutions end to end. Whether you need a predictive model, a RAG assistant, an AI agent, or AI features added to your product, you get an engineer who focuses on the outcome, not just the demo, backed by the wider Amilek team when a project needs more.
Common use cases include building predictive and forecasting models, creating AI chatbots and knowledge assistants that answer from your own data, fine-tuning models for a specific domain, and adding smart AI features into an existing app. It also covers automating manual work with AI and turning raw data into useful, reliable insights.
Our AI/ML engineers work with Python, PyTorch, TensorFlow, and Scikit-learn for models, and OpenAI, Claude, and Gemini for LLM features, with RAG, vector databases, and fine-tuning (LoRA, QLoRA) where needed. We use MLflow and DVC for reproducibility and FastAPI for serving, and we validate every solution against real data before it goes live.
Share the problem you want to solve and the outcome you are after, along with any data you have and where it lives. Let us know if you are adding AI to an existing product or building something new, and any constraints on budget or timeline. Example results you expect help us scope the work realistically.
