AI Engineer - Marquee Team - Dallas - GBM Public

What We Do:

At Goldman Sachs, our Engineers don’t just make things – we make things possible.  Change the world by connecting people and capital with ideas.  Solve the most challenging and pressing engineering problems for our clients.  Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.

Who We Look For:

Goldman Sachs has a unique and differentiated set of data, including proprietary content, analytics, and research; leveraging these unique datasets and content will enable the firm to double down on its existing strengths and harness the power of Generative AI.

Goldman Sachs is seeking an Applied AI Engineer to join Marquee in Global Banking & Markets. As an integral part of the team, you will play a pivotal role in driving the adoption of cutting-edge Generative AI technologies at the firm interacting directly with our business.

In this role, you will have the opportunity to contribute to various AI/ML domains, including but not limited to machine learning, deep learning, natural language processing, information retrieval, time series analysis, and recommender systems. You will help address the unique challenges that arise in machine learning systems within the financial domain. Join us in redefining the boundaries of what's possible in the intersection of quantitative research and artificial intelligence!

Responsibilities:

• Collaborating effectively with colleagues to advance production machine-learning systems and applications.
• Conceptualizing, experimenting with, and assessing AI/ML-based software systems.
• Developing, testing, and maintaining high-quality, production-ready code.
• Demonstrating technical leadership by taking charge of cross-team projects.
• Creating libraries and frameworks that underpin reliable and testable systems.
  Represent Goldman Sachs at conferences and within open-source communities.

Qualifications:

• A degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Physics, Engineering, Quantitative Finance, or equivalent relevant industry experience.
• A minimum of 2 years of experience in the industry that demonstrates your expertise.
• Extensive experience in software development for quantitative investment workflows in equities, fixed income, or multi-asset strategies.
• Proficiency in contemporary programming languages like Python, C++, or Java.