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BTP AI Data Scientist / Machine Learning Engineer

SAP

Join SAP as a BTP AI Data Scientist / Machine Learning Engineer

About the Role

SAP is seeking a passionate and innovative Data Scientist / Machine Learning Engineer to join our Business Technology Platform (BTP) AI team. This role is pivotal in shaping and delivering the future of Generative AI capabilities across our platform. You will be part of an international, multi-disciplinary AI team, working closely with architects, data engineers, UX designers, and more.

Key Responsibilities

  • Lead Cutting-Edge Research: Drive applied research, proof-of-concept projects, and technological exploration within our dynamic AI development team.
  • Collaborate Globally: Work with our global IT business technology team to tackle large-scale, complex challenges.
  • Innovate Solutions: Design, implement, and test advanced AI-powered systems to solve intricate business challenges.
  • Shape the Future of AI: Develop and enhance generative AI applications across various use cases.
  • Drive End-to-End Projects: Take ownership of comprehensive AI/ML projects, contributing beyond algorithm development.
  • Master AI Techniques: Utilize a broad spectrum of AI and Machine Learning techniques, managing all facets of the system including model architecture, pipeline automation, and metrics interpretation.
  • Validate and Innovate: Validate machine learning use cases through proof-of-concepts with Large Language Models.
  • Collaborate and Patent: Work closely with fellow AI Engineers and Architects, sharing knowledge and best practices, with opportunities to patent innovative solutions.

What You’ll Bring

  • Proven Experience: Over 3 years of experience as a Machine Learning Engineer or Data Scientist, ideally within business application software companies.
  • Generative AI Expertise: Strong understanding of Generative AI concepts and extensive knowledge of generative AI models, frameworks, and tools.
  • Programming Skills: Strong coding abilities in Python, Java, or TypeScript.
  • Technical Proficiency: Expertise in prompt engineering and tuning techniques such as chain-of-thoughts and RAG. Proficient in deep learning concepts and libraries like Scikit-learn, Numpy, Pandas, PyTorch, Generative Pre-Trained Transformer, and TensorFlow. Good knowledge with SQL.
  • Scalable Solutions: Experience in developing and productizing scalable AI solutions.
  • Agile Methodologies: Familiarity with Agile methodologies is preferred.
  • Innovative Mindset: Ability to introduce and execute new ideas effectively.
  • SAP Knowledge: Understanding of SAP technologies, including SAP BTP and SAP HANA.
  • Communication Excellence: Outstanding written and verbal communication skills in English.

Meet Your Team

SAP's Business Technology Platform is shaping the future of enterprise software, creating the ability to extend and personalize SAP applications, integrate, and connect entire landscapes, and empower business users to integrate processes and experiences. The BTP AI team is part of the T&I board area and part BTP foundation which also hosts a range of cross units for BTP. Our team aims to be on top of the latest advancements in AI and how we apply these to increase the platform value for our customers and partners.

Why SAP?

SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development.

SAP is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to the values of Equal Employment Opportunity and provide accessibility accommodations to applicants with physical and/or mental disabilities.

Join us to bring out your best and help the world run better.

Benefits
Extracted with AI

  • Flexible working models
  • Collaborative team environment
  • Learning and development opportunities
  • Recognition for individual contributions
  • Equal opportunity workplace

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