Senior AI/ML Engineer

Quick Facts

• Focus: agentic AI and LLM-powered systems plus classic ML engineering and MLOps

Description

Design, build, and deploy machine learning systems and agentic solutions that solve business problems. The role centers on LLM-powered agents that can reason, plan, and take autonomous actions across multiple AI platforms, combined with the full ML lifecycle—from data pipelines to production deployment.

Responsibilities

• Design and build agentic workflows using LLMs for autonomous multi-step task execution
• Build and deploy agentic solutions across multiple AI platforms/ecosystems and integrate tools via function calling
• Implement orchestration patterns (planner-executor, multi-agent collaboration, ReAct-style reasoning loops)
• Build retrieval-augmented generation (RAG) pipelines to ground outputs in proprietary/real-time data
• Create guardrails, evaluation harnesses, and monitoring for reliability, safety, and task success rates
• Prototype and iterate on agent behaviors using frameworks such as LangGraph, LlamaIndex, CrewAI, or custom orchestration layers
• Design workflows that consume structured outputs from perception/detection models (e.g., computer vision) to trigger downstream automation like alerts, corrective tasks, or automated reports
• Design, train, fine-tune, and evaluate ML/deep learning models for production use cases, including computer vision/object detection
• Build and maintain scalable data pipelines for training, validation, and inference
• Apply MLOps best practices: CI/CD for models, versioning, monitoring, and automated retraining
• Optimize model performance, latency, and cost for training and inference (including potential on-device/edge/mobile scenarios)
• Compare model-detected states against source-of-truth datasets and flag discrepancies for downstream automation
• Improve model accuracy using field/production feedback, labeled data pipelines, and active learning loops
• Integrate ML models and agents into production applications via robust, well-tested APIs
• Conduct offline/online evaluations and A/B tests to measure model and agent impact

Benefits

• Annual bonus
• Private medical care
• Cafeteria and multisport benefits
• English lessons subsidized by the company
• Group insurance
• Two additional days off (Good Friday, Friday after Corpus Christi) with the possibility to exchange for other holidays
• Employee referral bonus program
• Attractive discounts for products and services at company stations
• Employee stock purchase plan
• Employee Assistance Program (Lyra)
• Modern and convenient office (virtual tour available)
• Trainings and possibility to develop skills in a wide international environment