AI Native Engineering - SAP

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 rank 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 models and their 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 LLMs, LSTM, RNN, TensorFlow, H2O is an 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.