20 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Lead architecture decisions and engineering best practices for enterprise AI/ML solutions.
- Design, develop, deploy, and scale solutions for anomaly detection, fraud detection, recommendations, forecasting, ranking, predictive insights, and AI-powered business applications.
- Build AI-native applications using LLMs, 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 full AI/ML lifecycle, including experimentation, evaluation, deployment, monitoring, drift detection, retraining, observability, and performance optimization.
- Optimize AI/ML workflows across thousands of tenants to reduce latency, resource utilization, and operational costs.
- Define evaluation frameworks and success metrics for models, recommendations, ML applications, and GenAI applications.
- Partner with product managers, architects, data engineers, software developers, and business stakeholders to deliver scalable solutions.
- Mentor junior engineers, conduct code reviews, establish quality standards, and lead technical initiatives from inception through production.
- Drive proofs of concept, rapid prototyping, and adoption of emerging AI technologies.
Requirements
- 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.
- Proficiency in Python, Java, Go, or a similar programming language.
- Hands-on experience with anomaly and fraud detection, recommendation systems, classification, clustering, forecasting, ranking, and predictive modeling.
- Experience building GenAI applications with LLMs, embeddings, vector databases, RAG pipelines, context engineering, and agent frameworks.
- Experience with PyTorch, TensorFlow, Scikit-learn, XGBoost, and modern ML ecosystems.
- Strong knowledge of MLOps practices, including model registries, experiment tracking, feature stores, and automated validation frameworks.
- Proficiency in SQL and experience 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 leading large-scale, cross-functional technical initiatives through production deployment.
- Strong communication, stakeholder management, problem-solving, ownership, and collaboration skills.
Benefits
- Work location is SAP Labs, Whitefield, Bangalore.
- SAP offers flexible working models and emphasizes inclusion, health, and well-being.
- Accessibility accommodations are available for applicants with disabilities.
- Successful candidates may undergo background verification with an external vendor.
Categories
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.