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Bloomberg Machine Learning Jobs (NOW HIRING)

Sandbar

Machine Learning Engineer

Manhattan, NY · On-site

$120 - $190/hr

Stream has been featured in WSJ, Bloomberg, & Wired, and begins shipping in Summer '26. Join us in ... RESPONSIBILITIES This role involves developing software and machine learning algorithms for use in ...

GPTZero

Machine Learning Engineer

New York, NY · On-site

$150K - $250K/yr

What we're looking for At GPTZero, we ensure that machine learning models are created for the ... Additionally, you will be working with an experienced (eg. ex-Google, Meta, Microsoft, Bloomberg ML ...

New

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

We're hiring our Founding ML Engineer, the first full-time machine learning hire who will turn ... Integrate with professional financial data providers (Bloomberg, FactSet, Refinitiv, CapIQ)

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Bloomberg Machine Learning information

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$25.5K

$42.6K

$88K

How much do bloomberg machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for bloomberg machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is a Bloomberg machine learning engineer?

A Bloomberg Machine Learning Engineer is a specialist who develops and implements machine learning models and algorithms to solve complex financial problems using Bloomberg's vast datasets. They work closely with software engineers, data scientists, and business teams to improve data-driven products and services. Their responsibilities may include researching new machine learning techniques, optimizing existing models, and deploying solutions into Bloomberg's production systems. This role requires strong programming skills, experience with machine learning frameworks, and a solid understanding of financial markets.

How does a machine learning engineer at Bloomberg typically collaborate with data scientists and software engineers?

At Bloomberg, Machine Learning Engineers work closely with data scientists to translate research models into production-ready systems, ensuring scalability and efficiency within real-time financial applications. They also partner with software engineers to integrate machine learning models into Bloomberg’s technology stack, maintaining performance and data security standards. Regular collaboration through agile methodologies and cross-functional meetings is common, allowing team members to align on project goals and address technical challenges quickly. This team-oriented environment fosters innovation and provides opportunities for skill development across both engineering and data science disciplines.

What are the key skills and qualifications needed to thrive as a Bloomberg machine learning engineer, and why are they important?

To thrive as a Bloomberg Machine Learning Engineer, you need strong programming skills in Python or C++, a background in computer science or related field, and expertise in statistics and machine learning algorithms. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and version control systems like Git is essential, and advanced degrees or certifications in AI/ML are highly valued. Analytical thinking, problem-solving ability, collaboration, and effective communication are soft skills that set top performers apart. These competencies are crucial for building robust, scalable ML solutions that drive Bloomberg's data-driven products and maintain their industry-leading analytics.

What is the difference between Bloomberg Machine Learning vs Bloomberg Data Analyst?

AspectBloomberg Machine LearningBloomberg Data Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; experience with ML frameworksDegree in Economics, Finance, or related; strong analytical skills
Work EnvironmentDeveloping algorithms, modeling, coding in Python/RData collection, analysis, reporting, using Excel/SQL
Industry UsageBuilding predictive models for financial dataInterpreting data trends for investment decisions

Bloomberg Machine Learning focuses on developing algorithms and models to analyze financial data, requiring programming and technical expertise. Bloomberg Data Analysts interpret and report on data trends, emphasizing analytical skills and financial knowledge. Both roles are integral to Bloomberg's data-driven environment but differ in technical depth and daily tasks.

More about Bloomberg Machine Learning jobs

What states have the most Bloomberg Machine Learning jobs?

States with the most job openings for Bloomberg Machine Learning jobs include:

What job categories do people searching Bloomberg Machine Learning jobs look for?

The top searched job categories for Bloomberg Machine Learning jobs are:

Bloomberg Machine Learning jobs near you
Infographic showing various Bloomberg Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

Sandbar

Manhattan, NY • On-site

$120 - $190/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago

Job description

About Sandbar

Sandbar is an interface company in New York City. We aim to augment individuals so we can each think, act, and move more freely. Our team has built SW, ML, and HW products across Meta, CTRL-labs, Google, Apple, Fitbit, Peloton, and Equinox.

Our first product, Stream, is a self extension—a private voice ring and conversational interface. Stream has been featured in WSJ, Bloomberg, & Wired, and begins shipping in Summer '26.

Join us in creating technology that extends human thinking.

RESPONSIBILITIES

This role involves developing software and machine learning algorithms for use in human computer interface products. This includes designing system architectures involving large language models for conversational, information retrieval, and digital automation tasks. This also includes utilizing data science and statistical methods to analyze and optimize machine learning model performance across tasks. Lastly, this includes optimizing the aforementioned systems for latency, reliability, and cost. Telecommuting permitted. 3x/week in office required.

REQUIREMENTS

Requires a bachelor’s degree in computer science, engineering, data science or machine learning plus 2 years of experience as a machine learning engineer. Must also possess: 2 years building & deploying ML-based applications, including data curation and model training; 2 years of experience researching and developing applications based on large language models such as OpenAI GPT models or Anthropic Claude models, and open source models such as Meta Llama models; 2 years of experience in quantitative analysis based on data science; 2 years of experience in Python programming language; 2 years of experience building real-time applications utilizing ML models, such as real-time voice conversation via speech-to-text models, real-time image processing utilizing vision-language models, or other real-time ML-based systems in a professional context for internal tools or external products; 1 year of experience with AWS or GCP; 1 year of experience with Docker, TorchServe, AWS Lambda, or SageMaker; 1 year of experience developing retrieval augmented generation systems to improve the accuracy of information retrieval in applications utilizing large language models in a professional context for internal tools or external products; and prior experience in at least 1 startup-stage company (founding engineer to Series A company). Must be able to successfully complete competency-based interviews

FTE Benefits
  • Health, vision, and dental benefits
  • Company-sponsored 401(k)
  • Unlimited PTO and sick time
  • Early stage equity
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