EYAI Native Engineering-SAP
About this role
Your key responsibilities
- 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.
- Establish and maintain development standards/best practices
- 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
Skills and attributes for success
- 4+ years of experience in AI development.
- 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 AI 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.
Ideally, you’ll also have
- Expertise in Big Data, Data Modeling
- 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
Good to have (additionally)
- Experience with IBM services for AI/ML (WatsonX, Assistant, Discovery or other)
What we look for
- A self-starter, independent-thinker, curious and creative person with ambition and passion
EY | Building a better working world
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
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EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients.
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