AI Engineer

4 tygodni temu

Warszawa, mazowieckie, Polska ITDS Pełny etat 25 zł

As an AI Engineer you will be working for our client, a global leader in the banking industry, supporting digital transformation initiatives across multiple business units. You will design and implement AI-driven solutions that optimize decision-making, enhance customer experience, and improve operational efficiency. The role involves working on projects such as intelligent document processing, fraud detection, and predictive analytics, while collaborating with cross-functional teams. This position provides a unique opportunity to apply cutting-edge machine learning models and generative AI techniques in a highly regulated financial environment.


Your main responsibilities:

  • Design, develop, and deploy AI and machine learning models for banking use cases

  • Collaborate with business analysts and stakeholders to translate requirements into AI solutions

  • Integrate AI models into production systems, ensuring scalability and reliability

  • Monitor, evaluate, and improve the performance of deployed models

  • Work with structured and unstructured financial data to build predictive insights

  • Apply generative AI and natural language processing techniques to improve customer-facing services

  • Ensure compliance with data privacy, security, and regulatory standards in all AI solutions

  • Document processes, models, and frameworks to support transparency and knowledge sharing

  • Collaborate with DevOps teams to streamline MLOps and deployment pipelines

  • Stay up to date with emerging AI technologies and propose innovative applications


You’re ideal for this role if you have:

  • Minimum 4 years of experience as a Machine Learning Engineer or AI Engineer

  • Strong proficiency in Python and libraries such as TensorFlow, PyTorch, or Scikit-learn

  • Proven experience in building, training, and deploying machine learning models in production

  • Familiarity with NLP techniques and large language models (LLMs)

  • Experience working with cloud-based AI environments (AWS, Azure, or GCP)

  • Solid understanding of MLOps practices and tools such as MLflow or Kubeflow

  • Good knowledge of SQL and experience handling large datasets

  • Strong problem-solving skills and the ability to explain complex models to non-technical stakeholders

  • Fluency in English, both written and spoken

  • Excellent communication and collaboration skills across multidisciplinary teams

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