Senior AI Engineer – Financial Services and MLOps

Unleash the Power of Generative AI — Redefine the Future of Financial Services! Poland-based opportunity with hybrid work model. As a Senior AI Engineer – Financial Services and MLOps, you will be working for our client, a global leader in the banking industry. You will support digital transformation initiatives by designing innovative AI-driven solutions to optimize decision-making, enhance customer experience, and elevate operational efficiency. This role offers a chance to work on cutting-edge projects such as intelligent document processing, fraud detection, and predictive analytics, within a highly regulated financial environment. Your main responsibilities: Design, develop, and deploy AI and machine learning models tailored for banking use cases Collaborate with business analysts and stakeholders to translate business requirements into AI solutions Integrate AI models into scalable and reliable production systems Monitor, evaluate, and continuously improve model performance Work with structured and unstructured financial data to derive predictive insights Apply generative AI and natural language processing techniques to improve customer-facing services Ensure compliance with data privacy, security, and regulatory standards across all solutions Document processes, models, and frameworks to promote transparency and knowledge sharing Partner with DevOps teams to optimize MLOps and deployment pipelines Stay abreast of emerging AI technologies and identify innovative applications within the financial sector You're ideal for this role if you have: Minimum of 4 years of experience as an AI Engineer, Machine Learning Engineer, or Data Scientist Strong proficiency in Python and frameworks like TensorFlow or PyTorch Proven experience in building, training, and deploying ML models in a production environment 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 expertise in handling large datasets Strong problem-solving skills and the ability to communicate complex models to non-technical stakeholders Fluency in English (both written and spoken) and proficiency in Polish