ABOUT OUR ROLE

‍

Goldman Sachs is looking for an experienced Applied Researcher to join the AI Research team. As an Applied Researcher, you will be responsible for defining, designing, developing and evaluating language models for financial use cases. Your expertise in Machine Learning (ML) and Natural Language Processing (NLP) will be crucial for the development of AI-driven solutions in the financial domain, as well as for the research of applying state-of-the-art Language Modelling techniques.

‍

‍

YOUR IMPACT

In this role, you will have the chance to work with various teams across different divisions on groundbreaking projects that leverage Large Language Models (LLMs) and other NLP techniques to analyze and process a plethora of financial documents. As an Applied Researcher, you will address the specific challenges that arise when applying these techniques to the financial sector and push the state-of-the-art in AI for finance.

‍

‍

‍

RESPONSIBILITIES

• Create and implement scalable NLP-based solutions to enable business activities
• Perform experiments to evaluate and enhance the efficiency and effectiveness of existing models.
• Implement and analyze state-of-the-art NLP solutions and adapt them in a financial context.
• Develop, test, and maintain high-quality, production-ready code.
• Demonstrate technical leadership by taking charge of cross-team projects.
• Ar􀆟culate ideas and findings clearly in both spoken and writen forms across different departments.
• Represent Goldman Sachs at conferences and within open-source communities.
• Collaborate effectively with colleagues to advance production machine-learning systems and applications.

‍

‍

‍

QUALIFICATIONS

• A Bachelor’s, master’s or PhD degree in Computer Science, Machine Learning, Mathematics, Engineering, or equivalent relevant industry experience.
• Preferably 3 years AI/ML industry experience for Bachelor’s/Masters, 1 year for PhD with a focus on Language Models and NLP.
• Programming experience in Python and strong knowledge of data structures, algorithms, and so􀅌ware engineering practices.
• Excellent understanding of NLP techniques/algorithms, and experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Strong verbal and written communication skills.
• Curiosity, ownership and willingness to work in a collaborate environment.
• Prior experience in a finance industry is a plus

‍