About this role
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.
Engineering, which is comprised of our Technology Division and global strategist groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here.
Who We Look For
Goldman Sachs is seeking an Applied AI Researcher to join our dynamic Applied Artificial Intelligence (AI) Research team. As an integral part of the team, you will play a pivotal role in driving the adoption of cutting-edge AI and Machine Learning (ML) technologies at the firm.
In this role, you will have the opportunity to contribute to various AI/ML domains, including but not limited to generative AI, machine learning, deep learning, natural language processing, information retrieval, and time series analysis. As an experienced AI Researcher, 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!
Your responsibilities will include:
- 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 we seek:
- Strong hands-on experience building and maintaining large-scale Python applications.
- A Master's or Ph.D. degree in Computer Science, Machine Learning, Mathematics, Statistics, Physics, Engineering, Quantitative Finance, or equivalent relevant industry experience.
- A minimum of 5 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.
Other facts
About Goldman Sachs
We aspire to be the world’s most exceptional financial institution, united by our shared values of partnership, client service, integrity, and excellence.
Operating at the center of capital markets, we act as one firm, mobilizing our people, capital, and ideas to deliver superior results across our clients’ most complex challenges.
For 157 years, Goldman Sachs has delivered world-class execution on a global scale across our leading Global Banking & Markets and Asset & Wealth Management businesses.
Apprenticeship is central to our culture, with hands-on coaching and access to leaders who bring decades of experience and expertise. With office locations around the world, we offer a broad range of career opportunities to those who insist on excellence and thrive on performance.
Find our Social Media Disclosures here: gs.com/social-media-disclosures
What you'll do
- You will collaborate with colleagues to advance production machine-learning systems and applications, and conceptualize and assess AI/ML-based software systems. Additionally, you will demonstrate technical leadership and represent Goldman Sachs at conferences.
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