Senior Machine Learning Engineer - INT ABS – API Business Services

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Description

WHAT YOU'LL BUILD: As a Senior Machine Learning Engineer, you will contribute in spearheading architecture decisions and engineering best practices for AI/ML solutions. Lead the design, development, and deployment of enterprise-grade machine learning solutions focused on anomaly and fraud detection, intelligent recommendations, predictive insights, and AI-powered business applications. Design and operationalize ML systems across large-scale operational, transactional, telemetry, and time series business datasets using statistical, machine learning, and deep learning techniques. Build AI-native applications leveraging Large Language Models (LLMs), Retrieval Augmented Generation (RAG), semantic search, embeddings, vector databases, and agentic workflows. Develop scalable data pipelines, feature engineering frameworks, model training workflows, and real-time inference services. Own the end- to-end AI/ML lifecycle including experimentation, evaluation, deployment, monitoring, drift detection, retraining, observability, and performance optimization. Optimize and scale AI/ML workflows across thousands of tenants to reduce inference latency, infrastructure resource utilization, and operational costs. Partner with product managers, architects, data engineers, software developers and business stakeholders to translate business challenges into scalable AI/ML solutions. Mentor junior engineers and conduct code reviews while establishing quality standards. Define success metrics and evaluation frameworks for model performance, recommendation quality, ML application accuracy, and GenAI application reliability. Drive innovation through POCs, rapid prototyping, and adoption of emerging AI technologies. WHAT YOU BRING: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline 6-10 years of experience in Machine Learning Engineering, AI Engineering, Data Science, or related software engineering roles. Proficient in one of the following - Python, Java, Go, or similar languages. Hands-on experience with anomaly and fraud detection, recommendation systems, classification, clustering, forecasting, ranking, and predictive modeling. Applicable experience building GenAI applications using LLMs, embeddings, vector databases, RAG pipelines, context engineering, and agent frameworks. Experience with PyTorch, TensorFlow, Scikit-learn, XGBoost, and modern ML ecosystems. Robust knowledge of MLOps practices including CI/CD, model registries, experiment tracking, feature stores, and automated validation frameworks. Proficient SQL skills and experience working with large-scale structured and unstructured datasets. Knowledge of Markov chains, stochastic processes, and probabilistic modeling. Knowledge of SAP AI Core, SAP Generative AI Hub, SAP HANA Cloud Vector Engine, or SAP BTP services is highly desirable. Demonstrated success in leading large-scale, cross-functional technical initiatives from inception through production deployment. Great communication, stakeholder management, and problem-solving skills and Growth mindset, deep sense of ownership, and a collaborative attitude WHERE YOU BELONG: SAP Business AI Platform INT ABS – API Business Services works on Integration Suite, offering services such as SAP Business Accelerator Hub and SAP API Management for seamless enterprise connectivity. Integration Cell introduces a steadfast, SAP-managed runtime architecture with improved isolation, scalability, and performance. The team is also building many innovative enterprise-grade AI native applications and platform capabilities. You will work alongside AI engineers, platform engineers, architects, and product teams to create innovative solutions that operate at enterprise scale while maintaining high standards for reliability, performance, security, and responsible AI. Job Location - SAP Labs, Whitefield, Bangalore Equal Employment Opportunity (EEO) Statement Our company does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.

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