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Bloomberg Machine Learning Jobs (NOW HIRING)

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

Bloomberg, CapIQ). * Refine foundational MLOps practices: model versioning, CI/CD, workflow ... Exposure to time-series modeling, forecasting, or reinforcement learning. * Experience working with ...

Sandbar

ML Engineer, Audio

New York, NY · On-site

$180K - $250K/yr

Stream has been featured in WSJ, Bloomberg, & Wired, and begins shipping in Summer '26. Join us in creating technology that extends human thinking. About We're looking for a machine learning engineer ...

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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:
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 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.
Senior Software Engineer - Impact Analysis & ML

Senior Software Engineer - Impact Analysis & ML

Bloomberg LP

New York, NY • On-site

$134K - $176.70K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago

Job description

Senior Software Engineer - Impact Analysis & ML
Location
New York
Business Area
Engineering and CTO
Ref #
10051600
Description & Requirements
Want to build a leading analytics platform from scratch that powers critical decision-making and solves complex, real-world problems? Ready to join a team that works with open source, big data technologies, and machine learning algorithms to drive innovation? Join our Impact Analysis & ML team.
We are part of the Bloomberg Enterprise Connectivity & Analytics (ECA) organization, which connects thousands of enterprise clients to hundreds of Bloomberg applications, moving terabytes of financial data in a snap.
Our ECA Event Analytics group ingests billions of events daily from Connectivity. Serving dozens of engineering teams, and thousands of active client users, we are advancing our platform with cutting-edge analytics in real-time and providing consistent, high-quality user experience. We already support various data analysis pipelines running in production for critical business workflows.
Impact Analysis is a strategic initiative built with stakeholders to assess business impact in real time and provide critical insights during complex system events. We are investing in machine learning, knowledge graphs, and lakehouse architectures, to further enhance the platform's analytical and decision-support capabilities. There is tremendous potential to innovate and expand the solution across the stack by correlating metrics and reference data for service teams, engineering, senior management, and clients.
We are seeking a Senior Software Engineer to join our collaborative engineering team and lead the design and development of intuitive, high-performance user experiences for our platform. As a full stack team, you will work across both backend and frontend, building scalable services, APIs, and data-driven applications. You will play a key role in transforming real-time system data into actionable insights through performant and reusable components, including supporting the integration of machine learning-driven capabilities.
You will also contribute to distributed systems and data pipelines using open source technologies such as Apache Spark, Apache Kafka, Apache Iceberg, Trino, Argo, and Neo4j.
We trust you to:
  • Design and implement scalable, high-impact technical solutions that drive measurable business value.
  • Own end-to-end development of features and services, from design through production.
  • Partner with business stakeholders to translate requirements into intuitive solutions.
  • Explore and evaluate approaches to complex problems, including prototyping and proof-of-concept development.
  • Lead technical discussions, mentor junior engineers, and contribute to the team's technical direction.
  • Advocate for best practices in architecture, development workflows, and system reliability.

You will need to have:
  • 4+ years of professional experience designing, developing, and delivering production-grade software using Python, Java, Go or C++
  • Experience designing and building RESTful APIs and microservices
  • Familiarity with distributed data systems (e.g., S3, Hadoop, Spark, Kafka)
  • Strong problem solving and communication skills and ability to work independently and as part of a team.
  • A degree in Computer Science, Engineering, Mathematics, a related field, or equivalent experience.

We'd love to see:
  • Experience with an open table format (e.g., Apache Iceberg).
  • Experience with workflow orchestration tools (e.g., Argo, Airflow)
  • Familiarity with graph databases (e.g., Neo4j) and ontology-driven data modeling
  • Familiarity with ML-enabled production systems
  • Interest in tackling ambiguous problems and building systems from the ground up

Salary Range = 160,000 - 240,000 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.
Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.
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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

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