AI Engineer – pharmaceutical industry (f/m/x)

Nasze wymagania: Minimum 5 years of experience designing and maintaining production MLOps/LLMOps pipelines with CI/CD for models Hands-on expertise with AWS SageMaker, Kubeflow, or MLflow, including model monitoring, retraining, and drift detection Proficiency in production-level Python, including writing clean, testable, and well-documented code, APIs, and services Strong skills in containerizing models with Docker and orchestrating with Kubernetes, ensuring scalability and high availability Proven experience deploying LLM and Transformer models using HuggingFace and LangChain; experience with Portkey or Galileo is a plus Practical use of AWS services such as Lambda, EC2, and SageMaker, with collaboration across infrastructure and data engineering teams Solid understanding of distributed architecture, data streaming, and handling high-volume data in production environments Fluency in English Residing in Poland required Mile widziane: Fluent Polish required Pharma-related experience O projekcie: We are looking for an experienced AI Engineer to help us responsibly shape and govern the rapidly evolving ecosystem of AI-powered tools. This is a strategic, engineering-focused role for someone who can turn AI/ML models — including LLM-based solutions — into stable, scalable, and well-monitored production systems. If you have a hands-on mindset, feel confident working with infrastructure, pipelines, and automation, and understand the realities of operating in a regulated environment (pharma / GxP), you might be exactly who we’re looking for! Zakres obowiązków: Design, implement, and maintain end-to-end MLOps/LLMOps pipelines for CI/CD and monitoring of data quality AI models Build robust and scalable APIs and services for deploying and serving AI/ML models, including anomaly detection and predictive data quality scoring Integrate and leverage advanced AI tools such as LangChain, Portkey, Galileo, and HuggingFace Transformers to develop data quality agents and automated error classification Collaborate with Data Engineering and IT Operations teams to manage cloud infrastructure (AWS) for scalable model serving, monitoring, and automated retraining Implement systems for monitoring model performance, detecting data and model drift, and automating the model retraining loop Ensure high availability and performance of AI systems under high data ingestion loads on the central data surveillance platform Design and deploy AI systems in compliance with internal security policies and GxP regulatory standards Continuously improve MLOps architecture and processes to maintain the resilience of the data quality Oferujemy: Great Place to Work since 2015 - it’s thanks to feedback from our workers that we get this special title and constantly implement new ideas Employment stability - revenue of PLN 2.1BN, no debts, since 2006 on the market We share the profit with Workers - over PLN 76M has already been allocated for this aim since 2022 Attractive benefits package - private healthcare, benefits cafeteria platform, car discounts and more Comfortable workplace – class A offices or remote work Dozens of fascinating projects for prestigious brands from all over the world – you can change them thanks to Job Changer application PLN 1 000 000 per year for your ideas - with this amount, we support the passions and voluntary actions of our workers Investment in your growth – meetups, webinars, training platform and technology blog – you choose Fantastic atmosphere created by all Sii Power People