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    AI/ML Research Scientist - Palo Alto, United States - SAP

    SAP
    SAP Palo Alto, United States

    1 month ago

    SAP background
    Description

    We help the world run better

    At SAP, we enable you to bring out your best. Our company culture is focused on collaboration and a shared passion to help the world run better. How? We focus every day on building the foundation for tomorrow and creating a workplace that embraces differences, values flexibility, and is aligned to our purpose-driven and future-focused work. We offer a highly collaborative, caring team environment with a strong focus on learning and development, recognition for your individual contributions, and a variety of benefit options for you to choose from.

    Summary:

    At SAP, we integrate AI technology with extensive industry-specific data and deep process knowledge to create innovative AI capabilities for all SAP applications. Large Language Models (LLMs) hold immense potential to change the way we work and develop products. They are reshaping the landscape of Machine Learning across various domains.

    SAP AI Product Engineering is responsible for designing central frameworks and cloud services such as Joule, Generative AI Hub, AI Core, and Document Information Extraction as the AI foundation for embedded AI throughout our portfolio in addition to our efforts towards SAP's foundation models, both our own tabular business models and building on top of partner LLMs, and generative AI technologies.

    The Role:

    • Collaborate with senior AI scientists to research and develop novel approaches for building Foundation Models for structured data.
    • Design and implement scalable algorithms and architectures to process and analyze large-scale structured datasets efficiently.
    • Conduct experiments and perform rigorous evaluations to measure the performance and effectiveness of the developed models.
    • Exposure to using LLMs in multiple NLP tasks – RAG, In-Context Learning and Knowledge Graphs.
    • Optimize and fine-tune models to improve accuracy, scalability, and interpretability.
    • Stay up to date with the latest advancements in the field of Deep Learning, Foundational Models, and Generative AI.

    What you bring:

    • Bachelor's or master's degree in computer science, Artificial Intelligence, or other relevant disciplines. PhD is a plus.
    • Experience with Foundation Models or LLMs and their application in a business context.
    • Solid understanding of Machine Learning algorithms and techniques, particularly in the context of structured data.
    • Proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or similar.
    • Strong communication and collaboration skills, with the ability to work effectively in cross-cultural teams.

    #SAPAICareers

    Bring out your best

    SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. 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. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.

    We win with inclusion

    SAP's culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better and more equitable world.

    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. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team:

    For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.

    EOE AA M/F/Vet/Disability

    Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, age, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability.

    Compensation Range Transparency: SAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step toward demonstrating SAP's commitment to pay equity. SAP provides the hourly base salary rate range applicable for the posted role. The targeted range for this position is USD) USD. The actual amount to be offered to the successful candidates will be within that range, dependent upon the key aspects of each case which may include education, skills, experience, scope of the role, location, etc. as determined through the selection process. SAP offers limited benefits for employees hired into hourly or like roles subject to appliable plan/policy terms. A summary of benefits and eligibility requirements can be found by clicking this link: SAP North America Benefits.

    Requisition ID: | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid

    ​

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