Job Description

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 strategists 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 Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change and thrive in a fast-paced global environment.

Enterprise Technology Operations (ETO) is a Business Unit within Core Engineering focused on running scalable production management services with a mandate of operational excellence and operational risk reduction achieved through large scale automation, best-in-class engineering, and application of data science and machine learning. The Production Runtime Experience (PRX) team in ETO applies software engineering and machine learning to production management services, processes, and activities to streamline monitoring, alerting, automation, and incident management.  The team also builds and operates products for order management, disaster recovery testing, and developer onboarding.

TEAM OVERVIEW

The Machine Learning & Analytics team in PRX uses generative AI, deep learning, predictive modelling, anomaly

detection, time series forecasting and other statistical modelling techniques on big and fast data to reduce the risk

and cost of managing the firm’s massive compute infrastructure and applications.

ROLE AND RESPONSIBILITIES

The responsibilities of an individual in this role include: