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Bloomberg Machine Learning Jobs in New York (NOW HIRING)

Bloomberg LP

Model Validation Expert

New York, NY · On-site

... and machine learning models Excellent communication skills with ability to translate technical ... Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture ...

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

See New York salary details

$27.9K

$46.6K

$96.3K

How much do bloomberg machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for bloomberg machine learning in New York is $46,588.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,600.00 and $50,300.00 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.

What are popular job titles related to Bloomberg Machine Learning jobs in New York?

For Bloomberg Machine Learning jobs in New York, the most frequently searched job titles are:

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

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

Bloomberg Machine Learning jobs near you
Infographic showing various Bloomberg Machine Learning job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $46,588 per year, or $22.4 per hour.

Senior Software Engineer - AI Inference

Bloomberg L.P.

Manhattan, NY • On-site

$135K - $178K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 19 days ago

Bloomberg rating

9.4

Company rating: 9.4 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

11th of 245 rated software companies

Job description

Description & Requirements
Our team:
Join the team that is building the core infrastructure for AI at Bloomberg. The Bloomberg AI Inference Platform provides production-grade managed infrastructure for hosting, deploying, and serving all machine learning models, both predictive and cutting-edge generative models. We abstract away infrastructure complexity, empowering engineering teams to focus on creating intelligent applications with guaranteed scalability, performance, and governance. Our platform is built on the open-source KServe project, and the CNCS AI Inference team is a primary contributor to its development.
We'll trust you to:
  • Design and build scalable infrastructure for both online and offline inference workloads.
  • Lead integration of high-performance inference runtimes and serving frameworks, including TensorRT, vLLM, ONNX, and Triton.
  • Drive architecture and technical decisions across Bloomberg's inference platform, balancing latency, throughput, reliability, and cost.
  • Partner across engineering teams to improve model deployment, observability, and production performance.
  • Mentor junior engineers on system design, debugging, and performance optimization.

You'll need to have:
  • 5+ years of professional software engineering experience.
  • Experience designing, building, and operating production distributed systems.
  • Strong systems intuition and a track record of debugging and optimizing performance-critical services.
  • Ability to own problems end-to-end and quickly ramp up in unfamiliar technical areas.
  • 4+ years of demonstrated experience working with an object-oriented programming language.
  • A degree in Computer Science, Electrical Engineering, or equivalent practical experience.

We'd love to see:
  • Experience deploying and operating machine learning systems at scale.
  • Experience with inference optimization techniques such as batching, caching, request scheduling, or memory-aware serving.
  • Familiarity with PyTorch and GPU software stacks such as CUDA and NCCL.
  • Exposure to high-performance interconnects and distributed computing technologies such as NVLink, InfiniBand, or MPI.
  • Experience with Kubernetes and cloud-native infrastructure.
  • Experience with load balancing, request routing, or traffic management systems.

Representative projects:
  • Autoscaling a heterogeneous compute fleet to match supply and demand aross diverse inference workloads.
  • Building production-grade deployment pipelines to safely roll out new models to millions of users.
  • Developing new inference capabilities such as structured sampling, prompt caching, and advanced serving optimizations.
  • Analyzing observability data from real production workloads to improve latency, throughput, and resource efficiency.

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.

What Bloomberg employees say

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Benefits

Hours and flexibility

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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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