Applied AI Engineer, Global Banking & Markets, New York City

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 AI Quant Engineer to join our Equities Business . As an AI Quant engineer, you will leverage your expertise in quantitative analytics, statistics, and artificial intelligence to develop and implement AI-driven quantitative technologies with the goal to enhance revenue generation, capital saving, operational efficiency and foster innovation within the firm. In this role, you will have the opportunity to collaborate with various teams and divisions on pioneering projects that integrate artificial intelligence with quantitative finance. As an AI Quant engineer, you will tackle the unique challenges associated with embedding intelligence in the quant analytics domain. Join us in pushing the boundaries of what is possible at the intersection of quantitative finance and artificial intelligence! How You Will Fulfill Your Potential

• Design, implement, and deploy scalable AI models & agentic workflows to drive commercial outcomes.
• Lead rigorous experimentation and data-driven analysis to continuously improve AI model effectiveness for business use cases.
• Collaborate proactively with stakeholders across the equities business to accelerate the delivery of AI driven solutions to drive tangible commercial outcomes.
• Champion the development, testing, and maintenance of reliable, production-ready software solutions.

Qualifications

• A Master or Ph.D. degree in Computer Science, Machine Learning, Quantitative Finance, Mathematics, Physics, or equivalent relevant industry experience.
• A minimum of 1-3 years of AI/ML experience in the industry that demonstrates your expertise.
• Proficiency in contemporary programming languages like Python and/or Java.
• Excellent understanding of machine learning techniques and algorithms, and experience with common data science toolkits.
• Demonstrated curiosity, ownership, and a willingness to work in a collaborative environment.

Salary Range The expected base salary for this New York, New York, United States-based position is $150000-$225000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.

Benefits

Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here. We are looking for an AI Quant Engineer to join our Equities Business . As an AI Quant engineer, you will leverage your expertise in quantitative analytics, statistics, and artificial intelligence to develop and implement AI-driven quantitative technologies with the goal to enhance revenue generation, capital saving, operational efficiency and foster innovation within the firm. In this role, you will have the opportunity to collaborate with various teams and divisions on pioneering projects that integrate artificial intelligence with quantitative finance. As an AI Quant engineer, you will tackle the unique challenges associated with embedding intelligence in the quant analytics domain. Join us in pushing the boundaries of what is possible at the intersection of quantitative finance and artificial intelligence! Apply tot his job Apply To this Job