Senior AI Engineer
bayer
Job Description
- 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 AIsolutions 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 ofAI models into existing software systems and workflows, ensuring seamless functionality and optimal user experience.
- Direct the deployment of AI solutions into production environments, implementing best practices for version control, architecture, monitoring, and ongoing maintenance.
- Collaboration and Communication Maintain comprehensive documentation of AI models, algorithms, solution architecture and processes to ensure transparency and facilitate knowledge sharing within the team.
- Engage proactively with team members and stakeholders to gather requirements, provide insights, and deliver effective AI solutions that align with project goals.
- Communicate complex AI concepts and project results effectively to both technical and non-technical stakeholders, fostering understanding, collaboration, and informed decision-making.
- Research and Innovation Stay abreast of emerging AI trends, technologies, and methodologies, actively contributing to the enhancement of team capabilities and innovation.
- Conduct research and experimentation to explore new AI techniques and approaches,