Senior AI Engineer @ Bayer

1 day ago

Warszawa, Czech Republic Bayer Full time
  • Master’s or Ph.D. degree in Computer Science, Information Technology, Data Science, Artificial Intelligence or a related field or Bachelor’s with minimum 5 years experience
  • Proven experience as an AI Engineer, Machine Learning Engineer, or similar role
  • Experience in developing and deploying machine learning models and AI systems
  • Proficiency in programming languages such as Python or R
  • Strong knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn)
  • Experience with natural language processing (NLP), computer vision, or other AI techniques
  • Familiarity with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud)
  • Strong analytical skills and the ability to work with complex datasets.

Excellent problem-solving skills with a focus on developing innovative AI solutions       


For Digital Hub Warsaw, we are looking for:



Senior AI Engineer

A Senior AI Engineer leads the design, development, and implementation of artificial intelligence solutions that address specific business problems. Individuals in this role have extensive experience with machine learning models, natural language processing, computer vision, or other AI technologies. They collaborate closely with data scientists, data engineers, and cloud engineers to deliver AI solutions that drive business value.

,[AI Solution Development: Lead the design and development of innovative machine learning models and algorithms in cross functional teams to effectively address specific business challenges, Lead the implementation of scalable AI products, ensuring alignment with user requirements and strategic business objectives, Leverage state-of-the-art cloud technologies (e.g., AWS, Azure, Google Cloud) to optimize the industrialization of machine learning models and AI solutions for production deployment , Provide expert operational support and guidance for machine learning models and algorithms, ensuring their reliability and performance in production environments , Data Engineering , Lead the architecture and design of robust, scalable data pipelines in collaboration with data engineers, cloud engineers, and data scientists, enhancing data access and processing capabilities , Lead data preprocessing, ingestion, and transformation activities across hybrid environments (both on-premises and cloud), ensuring adherence to best practices and organizational standards, Establish and promote advanced data quality assurance processes, including validation checks and proactive data drift detection mechanisms, to ensure data consistency and integrity , Data Science , Mentor and guide team members in the model training process, focusing on industrialization through cloud technologies and achieving accuracy, reliability through experimentation and iterative improvements, Lead the evaluation and tuning of models, utilizing metrics and performance benchmarks to refine model parameters and enhance predictive capabilities , Integration and Deployment , Lead the integration of AI models into existing software systems and workflows, ensuring seamless functionality and optimal user experience.] Requirements: Azure, NLP, ML, Python, PyTorch, TensorFlow, Hadoop, AWS, Computer vision Tools: GitHub. Additionally: Sport subscription, Training budget, Private healthcare, Lunch card, International projects, Free coffee, Canteen, Bike parking, Playroom, Free snacks, Free beverages, Free parking, Modern office, In-house trainings.

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