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Freelance Machine Learning Quant Jobs (NOW HIRING)

Bracebridge Capital

Machine Learning Analyst

Boston, MA

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to ...

Qfanalytics

Machine Learning Engineer

Miami, FL · On-site

$80 - $120/hr

They'll be working on cutting edge Quantitative Data Analysis and Machine Learning challenges. Our environment is fast paced and constantly changing; the right candidate must be able to demonstrate ...

Qfanalytics

Machine Learning Engineer

Chicago, IL · On-site

$80 - $120/hr

They'll be working on cutting edge Quantitative Data Analysis and Machine Learning challenges. Our environment is fast paced and constantly changing; the right candidate must be able to demonstrate ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... machine learning solutions on the Snowflake Cloud data warehouse platform using the Snowpark ... quantitative/applied field (Engineering, Computer Science, Data Science, Operations Research ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to ...

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Freelance Machine Learning Quant information

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How much do freelance machine learning quant jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for freelance machine learning quant in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What is the difference between Freelance Machine Learning Quant vs Freelance Data Scientist?

AspectFreelance Machine Learning QuantFreelance Data Scientist
CredentialsStrong background in quantitative finance, mathematics, and machine learningBackground in statistics, data analysis, and programming; often less finance-specific
Work EnvironmentFinancial firms, hedge funds, or independent consulting in financeVarious industries including tech, healthcare, marketing, and finance
Industry UsagePrimarily in finance and trading

Freelance Machine Learning Quants focus on applying machine learning techniques to financial markets, often working with trading strategies and risk models. Freelance Data Scientists have a broader scope, working across multiple industries to analyze data, build predictive models, and generate insights. While both roles require strong technical skills, the finance-specific knowledge distinguishes the Freelance Machine Learning Quant from the Freelance Data Scientist.

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Freelance Machine Learning Quant jobs near you
Infographic showing various Freelance Machine Learning Quant 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 $99,230 per year, or $47.7 per hour.

Engineer, Machine Learning

Venture Global, Inc.

Arlington, VA • On-site

$157K - $185K/yr

Full-time

Posted 12 days ago

Job description

Venture Global LNG ("Venture Global") is a long-term, low-cost provider of American-produced liquefied natural gas. The company's Louisiana-based export projects service the global demand for North American natural gas and support the long-term development of clean and reliable North American energy supplies. Using reliable, proven technology in an innovative plant design configuration, Venture Global's modular, mid-scale plant design will replace traditional designs as it allows for the same efficiency and operational reliability at significantly lower capital cost.
We are seeking qualified applicants for the position:
Engineer, Machine Learning
Located:
Arlington
Summary
The Machine Learning Engineer will design, develop, and maintain the productionization of machine learning, deep learning, generative AI, large language models, simulation, and optimization algorithms. This includes building pipelines for training and deploying deep learning and other machine learning algorithms and enabling models to run efficiently in production. The main data engineering work will be done in Databricks and PySpark.
The ideal candidate will have excellent technical proficiency, excellent communication skills, a self-driven mindset, and the willingness to continuously learn new things.
This position will report to the Director of Business Intelligence and is structured within IT under the Vice President of Applications.
The position will be located in Arlington, VA and will require commuting to the office 5 days a week.
General Description Duties & Responsibilities
  • Work with business stakeholders to define project requirements.
  • Orchestrate, scale, setup and improve model serving pipelines.
  • Improve model accuracy through feature engineering, tuning, and observability.
  • Improve model computational performance through all aspects of the pipeline, including tuning clusters/job compute, partitioning, caching, feature engineering code, tuning setup, etc.
  • Integrate machine learning models into production environments, ensuring reliability and scalability.
  • Evaluate pretrained models and software from vendors and support integration into production environments.
  • Develop comprehensive project plans for implementing machine learning and AI projects including solution architectures, resourcing, and dependencies.
  • Provide ETL requirements to data engineers to effectively curate files for data analytics.
  • Work with data scientists, data engineers, and business analysts to translate business requirements into machine learning solutions.
  • Build software solutions that are maintainable, scalable and provide quantifiable business value.
  • Continuously focus on quality architecture, quality code, and ruthless management of technical debt.
  • Continuously push the practice forward, learning and testing newer and better ways of performing work.

Qualifications
Required experience
  • 5 years of machine learning engineering, software engineering, or data science experience.
  • Bachelors in a quantitative field of study.

Preferred Experience
  • Masters in a quantitative field of study.
  • Experience with the Azure, AWS, or other cloud ecosystems.
  • Experience in building secure data processing pipelines.
  • Proficient in utilizing data lakes, CI/CD pipelines, Databricks, Unity Catalog, and Git.
  • Experience working with streaming.
  • Expertise in building machine learning solutions using cloud data services.
  • Exceptional skills in data processing languages such as SQL, Python, or Scala.
  • Exceptional skills in feature engineering, model optimization, and parameter tuning.

Salary Range
$157,000-$185,000
Venture Global LNG is an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law.

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