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How much do goldman sachs machine learning jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for goldman sachs machine learning in the United States is $18.35, according to ZipRecruiter salary data. Most workers in this role earn between $15.87 and $20.19 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a machine learning professional at Goldman Sachs?

To thrive as a Machine Learning professional at Goldman Sachs, you need a solid background in computer science, statistics, and quantitative analysis, typically supported by an advanced degree in a related field. Expertise in programming languages such as Python or Java, experience with machine learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with financial data systems are essential. Strong problem-solving skills, effective communication, and the ability to collaborate across multidisciplinary teams set top candidates apart. These skills are crucial for creating innovative, reliable, and compliant data-driven solutions that drive business value in the fast-paced financial sector.

Is Goldman Sachs Machine Learning a high paying job?

A machine learning role at Goldman Sachs is typically a high-paying position within the finance and technology sectors, often offering competitive salaries and bonuses. Compensation depends on experience, skills, and performance, with roles requiring expertise in data analysis, programming, and financial modeling.

What do machine learning professionals at Goldman Sachs do?

Machine learning professionals at Goldman Sachs develop and implement algorithms that analyze large datasets to improve decision-making and automate processes across the firm. They work on projects ranging from risk assessment and fraud detection to trading strategies and client personalization. These roles involve close collaboration with engineers, data scientists, and financial experts to create innovative solutions that drive business value and efficiency. The work is highly dynamic and requires strong programming, statistical, and analytical skills.

What is the difference between Goldman Sachs Machine Learning vs Goldman Sachs Data Analyst?

AspectGoldman Sachs Machine LearningGoldman Sachs Data Analyst
Required CredentialsDegree in Computer Science, Data Science, or related fields; experience with ML algorithmsDegree in Finance, Economics, or related fields; proficiency in data analysis tools
Work EnvironmentFocus on developing ML models, programming, and algorithm optimizationData interpretation, reporting, and supporting decision-making processes
Employer & Industry UsageTech-driven roles within finance, emphasizing AI and automationFinancial services, emphasizing data reporting and analysis

Goldman Sachs Machine Learning roles primarily involve developing and implementing machine learning models, requiring technical skills in programming and algorithms. In contrast, Goldman Sachs Data Analysts focus on analyzing financial data, generating reports, and supporting business decisions. Both roles are integral to the firm's data-driven strategies but differ in technical depth and daily tasks.

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What cities are hiring for Goldman Sachs Machine Learning jobs? Cities with the most Goldman Sachs Machine Learning job openings:
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Goldman Sachs Machine Learning jobs near you
Infographic showing various Goldman Sachs Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $38,160 per year, or $18.3 per hour.

Compliance, Machine Learning Engineer, New York, Vice President

Goldman Sachs

New York, NY • On-site

Other

Re-posted 10 days ago

Goldman Sachs rating

8.3

Company rating: 8.3 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

47th of 170 rated banks

Job description

Are you passionate about delivering mission-critical, high quality machine learning models, using cutting-edge technology, in a dynamic environment? 

OUR IMPACT

We are Compliance Engineering, a global team of more than 300 engineers and scientists who work on the most complex, mission-critical problems. 

We:

  • build and operate a suite of platforms and applications that prevent, detect, and mitigate regulatory and reputational risk across the firm. 
  • have access to the latest technology and to massive amounts of structured and unstructured data.
  • leverage modern frameworks to build responsive and intuitive UX/UI and Big Data applications.

Within Compliance engineering, we are hiring for a Machine Learning Engineering role within Models Engineering. The firm is making a significant investment improve the precision/ recall of the Compliance models portfolio in 2024. To achieve that we are hiring experienced MLEs who have experience of developing and deploying ML models for big data in a distributed architecture.

HOW YOU WILL FULFILL YOUR POTENTIAL

As a member of our team, you will:

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

QUALIFICATIONS

A successful candidate will possess the following attributes:

  • 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 (algorithms, data structures, software design)
  • Expertise in Python & PySpark
  • Experience in working with distributed technologies like Scala, Pyspark, Iceberg, HDFS file formats (avro, parquet), AWS/ GCP,  big data feature engineering.
  • Experience in system design and evaluating the pros and cons of database choices, schema definition for data storage.
  • Extensive experience with Machine Learning and Deep Learning toolkits (Tensorflow, PyTorch, Scikit-Learn, HuggingFace)

Experience in some of the following is desired and can set you apart from other candidates : 

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

 
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. 

 
We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. 

 
We're committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

 

 
The Goldman Sachs Group, Inc., 2023. All rights reserved.
Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law

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About Goldman Sachs

Sourced by ZipRecruiter

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869

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