Expert AI & Data Science Engineer

We are looking for an Expert AI & Data Science Engineer - GenAI to join the IT team of our client - a company specialized in the Telecom sector.

What will be your main tasks and responsibilities?

- 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.

What will be required from you?

- Degree in Data Science, Computer Science, Statistics, or a similar area;

- At least three years of experience in building and deploying machine learning models, preferably 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;

- 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;

- Fluency in English both written and spoken.

Sounds like you? Send us your CV and let's talk!

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