Engineering - Machine Learning Software Engineer - London - VP

Goldman Sachs is looking for an experienced ML engineer to join the AI Research team. As an AI 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.

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 will include:

• Create and implement scalable AI/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.
• Articulate ideas and findings clearly in both spoken and written 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.

Required Qualifications:

• A Bachelor’s, Master's or PhD degree in Computer Science, Machine Learning, Mathematics, Engineering, or equivalent relevant industry experience.
• A minimum of 5 years AI/ML industry experience, preferably with a focus on Language Models and NLP.
• Programming experience in Python and strong knowledge of data structures, algorithms, and software 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 collaborative environment.