Compliance, Machine Learning Engineer, Dallas, Vice President

About the role

We are hiring for a Machine Learning Engineering role within Models Engineering in Compliance Engineering. The firm is making a significant investment to improve the precision and recall of the Compliance models portfolio in 2024. We seek experienced MLEs with a track record of developing and deploying ML models for big data in distributed architectures.

Our Impact

Compliance Engineering is a global team of over 300 engineers and scientists tackling the most complex, mission-critical problems. We build and operate platforms and applications that prevent, detect, and mitigate regulatory and reputational risk across the firm. The team has access to the latest technology and massive amounts of structured and unstructured data, leveraging modern frameworks to create responsive UIs and Big Data applications.

Responsibilities

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

Requirements

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

Preferred Qualifications

• Prior experience with LLMs and Prompt Engineering.
• Experience architecting or deploying ML applications on AWS/GCP.
• Experience with code reviews and architecture design for distributed systems.

About Goldman Sachs

Founded in 1869, Goldman Sachs is a leading global investment banking, securities, and investment management firm. Headquartered in New York, we maintain offices worldwide. We are committed to fostering diversity, inclusion, and professional growth through training, development opportunities, firmwide networks, benefits, wellness programs, and more. Learn more about our culture and people at GS.com/careers.