2 days ago
Budapest, HungaryEntry Level
Responsibilities
- Monitor customer-facing SAP Integrated Business Planning environments for performance, availability, and SLA adherence.
- Perform root cause and out-of-memory analysis for SAP HANA incidents and coordinate resolution with development teams.
- Monitor production ML model health across latency, correctness, usage, drift, and AI agent and ML pipeline performance.
- Build telemetry and observability pipelines to detect ML failures, regressions, and data quality issues.
- Develop Python automation for recurring site reliability engineering and ML operations workflows.
- Document RCA reports, runbooks, and standard operating procedures.
Requirements
- Hands-on experience with SAP HANA administration, memory management, SQL analysis, or performance tuning.
- Python scripting experience for automation, data analysis, and ML pipeline operations.
- Familiarity with ML model monitoring or MLOps, including model drift, latency tracking, and evaluation pipelines.
- Knowledge of SAP Business Technology Platform or equivalent enterprise cloud environments.
- Root cause analysis skills for complex, distributed systems.
- Practical experience using automation and AI tools, designing prompts, prototyping solutions, and validating AI-generated output quality.
- Fluency in English is required.
- A degree is not required.
Benefits
- Flexible working models are supported.
- The role involves up to 10% travel.
Categories
ML EngineeringSite Reliability
About SAP
SAP builds enterprise application software and cloud services for finance, procurement, supply chain, human resources, and analytics, sold through subscriptions, licenses, and support. Its portfolio includes SAP S/4HANA, SAP Business Technology Platform, SAP Ariba, and SAP SuccessFactors. Founded in 1972 and headquartered in Walldorf, Germany, SAP is a public company listed on the NYSE and Frankfurt (ETR) and serves enterprises and public-sector organizations worldwide.