AI Native Engineering - SAP

• 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)
• Experience in Agentic AI developments frameworks , protocols and Agent to agent interoperability.
• Interest in understanding functional and industry business challenges.

Ideally, youll 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