A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
12-18 Years We welcome candidates with all U.S. work authorization types, provided they are legally authorized to work in the United States. Key Responsibilities Design, develop, and implement scalable machine learning solutions on the Databricks platform leveraging SAP Business Data Cloud (SAP BDC). Develop robust, high-performance Python-based data pipelines to ingest, transform, analyze, and model large-scale SAP and non-SAP datasets. Ensure data pipelines provide strong data quality, scalability, and reliability. Build, train, evaluate, and deploy production-grade machine learning models. Develop AI/ML solutions that generate actionable business insights and enable intelligent automation across enterprise processes. Collaborate with business stakeholders, SAP functional experts, data engineers, and solution architects to identify AI/ML opportunities. Deliver end-to-end data-driven AI/ML solutions aligned with business requirements. Develop scalable, production-ready Python applications using modern AI/ML frameworks and software engineering best practices. Apply Finance domain knowledge to translate functional requirements into AI/ML use cases. Develop solutions supporting financial reporting, forecasting, planning, risk analysis, and operational efficiency. Required Skills 12-18 years of relevant professional experience. Strong expertise in Python and production-grade application development. Strong hands-on experience with Databricks. Experience designing and implementing scalable Machine Learning solutions. Experience building, training, evaluating, and deploying production-grade ML models. Strong experience developing scalable Python-based data pipelines. Experience working with large-scale SAP and non-SAP datasets. Experience with SAP Business Data Cloud (SAP BDC). Strong understanding of data quality, scalability, and reliability considerations. Experience with modern AI/ML frameworks and software engineering best practices. Strong collaboration skills across business, SAP functional, data engineering, and architecture teams. Strong Finance domain knowledge.
Mandatory Skill:
SAP BW IP.
Preferred Experience Experience delivering AI/ML solutions within SAP-centric enterprise environments. Experience integrating SAP and non-SAP data within Databricks. Experience applying machine learning to financial reporting, forecasting, planning, and risk analysis. Experience developing AI-driven business capabilities and intelligent automation solutions. Experience working with cross-functional enterprise teams on end-to-end data and AI/ML initiatives. We are committed to fostering an inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by applicable law.
