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Bloomberg Machine Learning Jobs (NOW HIRING)

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 ...

Associate Manager Machine Learning

Irvine, CA · Hybrid

$134.50K - $158.30K/yr

We are hiring a Manager, Machine Learning (MLE) to lead the development and operationalization of ... Yum! also received widespread recognition in 2023, including being listed on the Bloomberg Gender ...

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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 May 29, 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 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.

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 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.

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:
Infographic showing various Bloomberg Machine Learning job openings in the United States as of May 2026, with employment types broken down into 1% Internship, 40% Full Time, 54% Part Time, 4% Contract, and 1% Nights. Highlights an 18% Physical, and 82% Hybrid job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Applied Machine Learning Engineer - Media Search and Recommendation

Applied Machine Learning Engineer - Media Search and Recommendation

Bloomberg LP

New York, NY • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago


Job description

Applied Machine Learning Engineer - Media Search and Recommendation
Location
New York
Business Area
Engineering and CTO
Ref #
10049313
Description & Requirements
Our Team
Bloomberg Media empowers global business leaders with breaking news, expert opinion and proprietary data distributed with global reach. With millions of unique visitors each month, our flagship website bloomberg.com is the go-to destination for those looking to stay ahead of the curve. As one of the top 10 most visited financial and news sites on the web, we take pride in delivering top-quality content that our audience can trust.
The Search and Personalization team owns the core discovery experiences on Bloomberg.com and the Bloomberg mobile app. We are responsible for how users search for, discover, and engage with content across a global audience, with a strong focus on personalization and recommendations. By powering Bloomberg's discovery hub, we play a critical role in helping users find the content that matters most to them, ensuring experiences are relevant, timely, and high quality. Our systems operate at web scale and sit at the intersection of backend services, data pipelines, and user-facing experiences. We are looking for a dedicated and experienced Machine Learning engineer to join the team. The ideal candidate will have a passion for Machine Learning, building distributed web scale systems and partnering with a variety of stakeholders within our expansive organization.
What's in it for you
As a senior engineer on the Search and Personalization team, you will play a key role in expanding Bloomberg Media's investment in personalization. You'll work closely with product managers, data scientists, and machine learning engineers to design and build systems that power personalized discovery experiences for millions of users.
You'll have ownership over impactful projects, from shaping technical direction to delivering production systems. The role offers a mix of backend, data, and potentially some frontend work, giving you the opportunity to influence the personalization models that deliver results to users. You'll be working on systems that are central to Bloomberg Media's growth and directly visible to a global audience.
We'll trust you to
• Lead the design and delivery of personalization and recommendation systems that power discovery across Bloomberg.com and mobile platforms.
• Build and maintain data pipelines that support personalization, experimentation, and model-driven product experiences.
• Design, develop, and evolve backend services and APIs that deliver personalized content at scale with low latency.
• Partner closely with the data science team to productionize models and enable rapid experimentation.
• Collaborate across the stack, including with frontend engineers, to deliver cohesive and high-quality user experiences.
• Make architectural decisions, drive technical discussions, and help set technical direction for the personalization platform.
• Mentor other engineers and raise the overall technical bar of the team.
You need to have
• 5+ years of industry experience in an Object Oriented Programming language, preferably Python or Java
• 5+ years of industry experience working with large data sets, performing machine learning model experimentation, implementation and deployment.
• A Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent professional experience.
We'd love to see
• Exposure building and developing a content recommendation system, focusing on recommendation algorithms and machine learning capabilities
• Familiarity building user behavioral models to predict users likelihood to perform high value actions like propensity to subscribe or churn
• Experience with end-to-end machine learning projects, including data analysis, feature engineering, model selection, hyper-parameter tuning, model deployment and ongoing performance monitoring.
• Hands-on expertise with big data systems and distributed data processing technologies such as Spark
• Proven track record building and maintaining data pipelines that power customer-facing product features.
• Demonstrated leadership delivering machine learning projects from inception through delivery.
• Practical expertise with public cloud platforms such as AWS.
• Proven ability to operate and evolve web-scale distributed systems in production.
Salary Range = 165,000 - 260,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
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About Bloomberg

Sourced by ZipRecruiter

Bloomberg runs on data. As the Data Management & Analytics team within Engineering, we support our organization's needs around managing data efficiently. The vision of the team is to build solutions that drive data quality, data dictionary, data stewardship, data lineage, reference, and master data management across various data domains (prospect, customer, vendor, material etc.). We partner with business teams across the organization in addressing their data needs and ultimately helping run business operations efficiently and make improved decisions.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1981