AI Engineer

bayer

Bengaluru, India 5 Years Exp Posted 1h ago

Job Description

  1. AI Solution Development
  • Collaborate with cross-functional teams to design and develop innovative machine learning models and algorithms that address specific business challenges.
  • Implement scalable AI products, ensuring they meet user requirements and business objectives.
  • Utilize state-of-the-art cloud technologies (e.g., AWS, Azure, Google Cloud) to industrialize machine learning models and AI solutions for deployment in production environments.
  • Provide operational support and guidance for machine learning models and algorithms, ensuring their reliability and performance in production settings.
  1. Data Engineering
  • Partner with data engineers, cloud engineers, and data scientists to design and deliver robust, scalable data pipelines that facilitate data access and processing.
  • Assist in data preprocessing, ingestion, and transformation activities across hybrid environments (both on-premises and cloud).
  • Implement and maintain data quality assurance processes, including validation checks and data drift detection mechanisms, to ensure data consistency and integrity.
  1. Data Science
  • Support the model training process, focusing on industrialization through cloud technologies and achieving accuracy, reliability through experimentation and iterative improvements.
  • Assist in the evaluation and tuning of models, utilizing metrics and performance benchmarks to refine model parameters and enhance predictive capabilities.
  1. Integration and Deployment
  • Aid in the integration of AI models into existing software systems and workflows, ensuring seamless functionality and user experience.
  • Contribute to the deployment of AI solutions into production environments, following best practices for version control, architecture, monitoring, and maintenance.
  1. Documentation and Reporting
  • Maintain comprehensive documentation of AI models, algorithms, and processes to ensure transparency and facilitate knowledge sharing within the team.
  • Prepare and present regular reports on AI project status, outcomes, and insights to stakeholders, highlighting key findings and recommendations for future work.
  1. Collaboration and Communication
  • Engage with team members to gather requirements, provide insights, and deliver effective AI solutions that align with project goals.
  • Communicate complex AI concepts and results in a clear and concise manner to non-technical stakeholders, fostering understanding, collaboration, and informed decision-making.
  1. Research and Innovation
  • Stay abreast of emerging AI trends, technologies, and methodologies to contribute to team capabilities.
  • Conduct research and experimentation to explore new AI techniques and approaches, providing insights that can inform future projects.

 

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