Compliance, Machine Learning Engineer, Dallas, Vice President

Goldman Sachs Compliance Engineering is seeking an experienced Machine Learning Engineer to develop and deploy scalable ML models for regulatory and reputational risk management. You will work with large-scale structured and unstructured data, lead end-to-end ML projects, and collaborate with researchers.

• Work with large-scale structured and unstructured data
• Drive end-to-end Machine Learning projects with high scale and complexity
• Build infrastructure for ML including feature engineering and scaling models
• Develop, productionize, and maintain ML models
• Run ML experiments, tune features and modeling approaches, document findings
• Collaborate with ML researchers to accelerate adoption of cutting-edge models
• Perform code reviews and ensure code quality

• Bachelor's or Master's degree in Computer Science or related field
• 10+ years hands-on experience building scalable machine learning systems
• Solid coding skills and strong CS fundamentals (algorithms, data structures, software design)
• Expertise in Python & PySpark
• Experience with distributed technologies: Scala, PySpark, Iceberg, HDFS (avro, parquet), AWS/GCP, big data feature engineering
• Experience in system design and evaluating database choices, schema definition