ai & automation expert.

• Develop and operationalize machine learning and generative AI models for high-impact business use cases;


• Design and implement data science models, including feature engineering and rapid prototyping;


• Build and automate AI pipelines, integrating them into business processes and tools;


• Manage the full AI lifecycle, including MLOps, monitoring, retraining, and governance alignment;


• Design and deploy GenAI applications for use cases such as content summarization, intelligent document processing, and chatbot assistants;


• Ensure performance optimization and cost-efficiency of AI models in cloud environments;


• Collaborate with data engineers and architects to align AI components with enterprise data architecture;


• Work closely with BI and automation teams to operationalize AI insights across platforms;


• Contribute to the standardization of reusable GenAI components, prompts, and evaluation techniques;


• Ensure alignment with responsible AI guidelines, data privacy requirements, and IT security standards;


• Translate complex AI models into actionable business insights through compelling storytelling;


• Monitor new trends in GenAI and identify opportunities for innovation and impact.

• Strong foundation in data science and machine learning, including traditional ML and GenAI use cases, with hands-on experience in applying these techniques to real-world business problems;


• Ability to identify and prioritize AI opportunities based on business value and feasibility;


• Proven ability to develop, fine-tune, and integrate generative models (LLMs, etc.);


• Experience with prompt engineering, retrieval-augmented generation (RAG), and LLM evaluation;


• Solid grasp of model lifecycle management, versioning, and performance tracking;


• Experience with cloud-based deployment and integration of AI into business workflows;


• Strong stakeholder communication skills, including the ability to explain AI/GenAI capabilities and limitations;


• Curiosity, adaptability, and a drive to stay ahead of AI innovation trends

Must Have:

• A successfully completed Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field;


• At least three years of hands-on experience in building and deploying machine learning models, including a minimum of two years working with cloud-based AI services, preferably on Google Cloud Platform (e.g. Vertex AI, AutoML, BigQuery ML);


• Strong proficiency in Python, with experience in ML and GenAI libraries (e.g. scikit-learn, TensorFlow, Hugging Face, OpenAI SDK);


• Experience developing and deploying LLM-based applications (chatbots, summarizers, semantic search);


• Knowledge of MLOps and GenAIOps workflows, model retraining, and monitoring;


• Understanding of GenAI architectural patterns such as RAG, agentic workflows, and embedding stores
  Strong command of SQL and working with structured and semi-structured data;


• Familiarity with APIs and tools for integrating GenAI capabilities into enterprise applications;


• Extensive professional experience in distributed, multinational and complex organizations;


• Fluent English (C1) skills written and spoken

Excellent opportunity to join a leading company, with the possibility of professional development.