The Machine Learning Engineering role within Compliance Engineering at Goldman Sachs focuses on developing and deploying high-quality machine learning models to address complex regulatory challenges. The team is composed of over 300 engineers and scientists dedicated to leveraging cutting-edge technology and vast data resources. In 2024, the firm aims to enhance the precision and recall of its compliance models, necessitating experienced professionals in the field. Candidates will work in a dynamic environment that emphasizes collaboration and innovation.

• A Bachelor's or Master's degree in Computer Science or a similar field of study.
• 10+ years of hands-on experience with building scalable machine learning systems.
• Solid coding skills and strong Computer Science fundamentals including algorithms, data structures, and software design.
• Expertise in Python and PySpark.
• Experience with distributed technologies like Scala, PySpark, Iceberg, and HDFS file formats.
• Familiarity with AWS or GCP and big data feature engineering.
• Experience in system design and evaluating database choices and schema definitions.
• Extensive experience with Machine Learning and Deep Learning toolkits such as TensorFlow, PyTorch, Scikit-Learn, and HuggingFace.

• Work with large scale structured and unstructured data.
• Drive end-to-end Machine Learning projects that have a high degree of scale and complexity.
• Build infrastructure for machine learning, including feature engineering and scaling models.
• Develop, productionize, and maintain machine learning models.
• Run ML experiments by tuning features and modeling approaches while documenting findings.
• Collaborate closely with ML researchers to accelerate the usage of cutting-edge models.
• Perform code reviews and ensure code quality.

• Employees at Goldman Sachs are often offered comprehensive benefits, including medical, dental, life and disability coverage, generous vacation and holidays, and robust wellness resources such as EAP counseling, medical advocacy, on-site/virtual health services, and fitness support. Financial perks typically include retirement savings programs, live financial education, education support, and wealth-creation opportunities through equity awards and select investment programs. Many locations also provide family benefits (childcare resources, parental and family leaves, adoption/surrogacy support) and flexible work options like part-time schedules, job sharing, telecommuting, and alternate hours.