Overview:

We are seeking a Lead AI Engineer (LLMs & Data Pipelines) to drive the design, integration, and operational excellence of LLM-powered capabilities across our platforms.

In this role, you will build intelligent features such as classification, extraction, summarization, and action orchestration powered by large language models. You will design embedding and retrieval pipelines (RAG, semantic search), create robust data pipelines for training and evaluation, and define clear evaluation metrics and quality gates to ensure reliable LLM behavior in production.

You will work hands-on with inference runtimes such as ONNX Runtime and TensorFlow Lite, benchmarking performance across CPU, GPU, NPU, and DSP environments, and optimizing deployments for latency, cost, and reliability—including in constrained or embedded systems. Collaborating with engineering, data, and MLOps teams, you will integrate models into real-world APIs and production systems while continuously experimenting with prompts, architectures, and model choices.

If you are passionate about turning advanced AI research into scalable, production-ready systems and efnjoy balancing performance, accuracy, and operational constraints, this may be your next mission.

What will you do?

• Build and integrate LLM-powered features (classification, extraction, summarization, actions).

• Integrate models with inference runtimes (such as ONNX Runtime, TensorFlow Lite / LiteRT).

• Benchmark and validate model performance across different hardware backends (CPU, GPU, NPU, DSP).

• Design embedding and retrieval pipelines (RAG, semantic search).

• Create and maintain data pipelines for training and evaluation.

• Define evaluation metrics and quality gates for LLM behavior.

• Optimize inference for latency, cost, and reliability.

• Integrate models into production systems and APIs.

• Run experiments to evaluate prompts, models, and architectures.

What are we looking for?

• Strong experience with LLMs and NLP systems

• Hands-on experience with embeddings and vector databases

• Strong Python skills and ML frameworks

• Experience building production data pipelines

• Solid understanding of evaluation and regression detection

• Experience with RAG architectures

• MLOps or monitoring experience 

• Experience with model calibration and accuracy/latency trade-off analysis

• Hands on experience deploying models on edge or embedded devices (constrained environments) 

What can you expect from us?

• A permanent job contract for a long term project;
• Tech equipment + SIM Card + personal smartphone;
• Health and Life Insurance;
• Social events and team buildings;
• The commitment of letting you grow with us, and be rewarded accordingly;
• A dynamic and young team that will be always there to support you;
• Training in the latest technologies;
• Coffee, fruits, snacks and a warm welcoming when you pass by the office.