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EY Client Technology-GEN AI Developer Insurance Industry Cloud 
India, Karnataka, Bengaluru 
239231777

10.09.2024

Your key responsibilities

  • Monitor technology trends and perform R&D activities in AI/ML area.
  • Assist in the collection and documentation of users’ requirements, development of user stories, estimates and work plans
  • Ensure modern AI/Gen AI best practices are applied
  • Develop, validate and deploy AI models.
  • Cooperate with architects to design the system
  • Establish and maintain development standards/best practices
  • Present effects of work to different stakeholders (e.g., demo)
  • Analyze the ML algorithms that could be used to solve a given problem and ranking them by their success probability.
  • Share the knowledge on the best ML Engineering practices with the team
  • Define validation strategies for ML solutions.

Skills and attributes for success

  • 7+ years of experience in ML development and MLOps.
  • Strong programming skills, with expertise in languages like Python with a good knowledge of ML, Data and API libraries.
  • Expertise in creating end-to-end data pipelines (sourcing, exploration, automation, etc.)
  • Experience with ML model and its development.
  • Should have knowledge in ModelOps/MLOps, AutoML, AI Ethics, Trust and Explainable AI
  • Understanding of some of the popular ML frameworks such as SparkML, Tensorflow, scikit-learn, XGBoost, H2o etc.
  • Experience working in a cloud environment (SAP, AWS, Azure, GCP) or a containerized environment (Mesos, Kubernetes)
  • Interest in understanding functional and industry business challenges
  • Desirable to have knowledge of Insurance Industry and potential GenAI use case in insurance processes

Ideally, you’ll also have

  • Expertise in Big Data, Data Modelling
  • Experience working with SAP platforms SAP AI Core, SAP Data Intelligence, Embedded Analytics in S/4HANA or SAP Analytics Cloud
  • Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
  • Verifying data quality, and/or ensuring it via data cleaning
  • Defining data augmentation pipelines
  • Training models and tuning their hyperparameters

Experience

  • Experience in LLM's, LSTM, RNN, Tensorflow, H2O are added advantage
  • Experience in deploying AI/ML platforms on Kubernetes and Containerization
  • Experience working with large data sets leveraging distributed systems e.g. Spark/Hadoop.
  • Experience in managing AI/ML cluster features like API endpoints management, Security, SSO, Auditing, version control, etc

What we look for

  • A self-starter, independent-thinker, curious and creative person with ambition and passion



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