Vice President, Compliance, Machine Learning Engineer

Goldman Sachs

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Work type
On-site
Location
New York, NY
Posted
1 day ago

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How this pay compares to similar roles

Similar $194k
$132k most similar roles pay here $241k

This listing doesn't post a salary. Most similar roles pay $157,000–$230,631.

Based on 240 similar postings.

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About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.

Goldman Sachs currently has 187 open roles on FindRole.

Listed pay typically runs $130,000–$250,000 across 60 roles with salary data.

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At a glance

TL;DR · Vice President, Compliance, Machine Learning Engineer

Join the Models Engineering team within Compliance Engineering as a Senior Machine Learning Engineer, contributing to the firm’s mission of enhancing the precision and recall of its compliance models. You will work with large-scale structured and unstructured data, driving complex end-to-end ML projects, building scalable infrastructures for feature engineering, and deploying machine learning models in distributed architectures. Your responsibilities include running experiments, collaborating with researchers, performing code reviews, and ensuring high-quality software practices. The role requires expertise in Python, PySpark, TensorFlow, PyTorch, and HuggingFace, along with experience in AWS/GCP, Scala, Iceberg, and big data feature engineering. Ideal candidates have a strong background in computer science fundamentals and 10+ years of hands-on experience in building scalable ML systems.

What you'll do

  • Drive end-to-end machine learning projects involving large-scale structured and unstructured data.
  • Build infrastructure for machine learning, including feature engineering and scaling models to work at scale.
  • Develop, productionize, and maintain ML models in a distributed architecture.
  • Conduct ML experiments by tuning features and modeling approaches, documenting results.
  • Collaborate with ML researchers to implement cutting-edge models.

What we're looking for

  • 10+ years of hands-on experience building scalable machine learning systems.
  • Strong expertise in Python, PySpark, and modern ML/DL toolkits like TensorFlow and PyTorch.
  • Solid coding skills with a deep understanding of computer science fundamentals.
  • Experience working with distributed technologies including Scala, Pyspark, Iceberg, HDFS file formats.
  • Extensive experience in system design and evaluating database choices for data storage.

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