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Machine Learning Quant Jobs (NOW HIRING)

This job will validate and develop machine learning models and algorithms to solve complex problems ... Conduct quantitative and qualitative model validation according to Model Risk Management Policy to ...

This job will validate and develop machine learning models and algorithms to solve complex problems ... Conduct quantitative and qualitative model validation according to Model Risk Management Policy to ...

This job will validate and develop machine learning models and algorithms to solve complex problems ... Conduct quantitative and qualitative model validation according to Model Risk Management Policy to ...

IMC Trading is seeking quantitative researchers with a proven track record to apply state-of-the-art machine learning & deep learning to solve challenging trading problems. This role is part of a ...

Strong interest in quantitative finance * Expert programming skills * Publication record in machine learning or quantitative finance (preferred) * Ability to communicate complex ideas clearly to ...

Strong interest in quantitative finance * Expert programming skills * Publication record in machine learning or quantitative finance (preferred) * Ability to communicate complex ideas clearly to ...

Strong interest in quantitative finance * Expert programming skills * Publication record in machine learning or quantitative finance (preferred) * Ability to communicate complex ideas clearly to ...

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Machine Learning Quant information

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$52.5K

$119.2K

$196.5K

How much do machine learning quant jobs pay per year?

As of Jun 7, 2026, the average yearly pay for machine learning quant in the United States is $119,165.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,500.00 and $152,500.00 per year, depending on experience, location, and employer.

What is a Machine Learning Quant job?

A Machine Learning Quant is a specialist in quantitative finance who applies machine learning techniques to develop trading strategies, manage risk, and analyze financial data. They leverage statistical models, deep learning, and reinforcement learning to identify patterns in market data and optimize predictions. This role typically involves programming in Python or C++, working with large datasets, and collaborating with traders and researchers. Machine Learning Quants are employed by hedge funds, investment banks, and proprietary trading firms to gain a competitive edge in financial markets.

What are the key skills and qualifications needed to thrive in the Machine Learning Quant position, and why are they important?

To thrive as a Machine Learning Quant, you need strong skills in quantitative analysis, programming (often in Python or C++), statistical modeling, and a solid foundation in applied mathematics, typically supported by a degree in a quantitative field such as mathematics, physics, computer science, or engineering. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), financial data platforms, and certifications such as CFA or advanced degrees can be advantageous. Critical thinking, collaboration, and clear communication are key soft skills that enhance effectiveness in working with both technical and non-technical stakeholders. These competencies are crucial for building and validating models that inform high-stakes financial strategies and deliver value in fast-paced trading environments.

What are typical daily responsibilities for a Machine Learning Quant in a financial firm?

As a Machine Learning Quant, your day often involves researching and developing predictive models using large financial datasets, backtesting quantitative strategies, and optimizing algorithms for speed and accuracy. You'll collaborate closely with traders, data engineers, and other quants to implement models in live trading environments and refine them based on performance feedback. Regular activities also include monitoring new data sources, adjusting to changes in the market, and documenting your methodologies for regulatory or team review. This multidisciplinary work environment offers the opportunity to continuously learn and directly impact trading outcomes.

More about Machine Learning Quant jobs
What are the most commonly searched types of Machine Learning Quant jobs? The most popular types of Machine Learning Quant jobs are:
What states have the most Machine Learning Quant jobs? States with the most job openings for Machine Learning Quant jobs include:
Infographic showing various Machine Learning Quant job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $119,165 per year, or $57.3 per hour.
Machine Learning Engineer

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 26 days ago


Job description

Radiance is seeking a Machine Learning Engineer who will advance the artificial intelligence capabilities of the National Air and Space Intelligence Center at Wright Patterson Air Force Base. This engineer will provide expertise in data analytics and algorithm development supporting the integration and analysis of diverse data sources and develop machine learning, data mining and statistical algorithms for pattern recognition and anomaly detection. Additionally, this position will improve upon current methods for the automated processing and exploitation of large data sets. This will include R&D on projects involving the exploitation of data from sensors including investigation of state-of-the-art machine learning classification methods to detect, track, and characterize targets of interest.

Radiance Technologies is an employee-owned company with benefits that are unmatched by most companies in the Dayton OH area. Employee ownership, generous 401K, full health/dental/life/vision insurance benefits, interesting assignments, educational reimbursement, competitive salaries and a pleasant work environment combine to make Radiance Technologies a great place to work and succeed.

Required Experience:

  • A working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)

  • Experience in applying core Machine Learning methodologies: Regression, Classification, Clustering, Decision Trees, Dimensional Reduction, Neural Networks & Deep Learning, Feature Engineering

Required Skills & Qualifications:

  • Bachelor's Degree in a quantitative field such as Physics, Engineering, Computer Science, Statistics, or a related field

  • Strong programming skills in at least one of the following languages Python, Matlab, C++

  • Experience with Machine Learning APIs, such as TensorFlow, PyTorch, or Keras

  • Active Secret Clearance with ability to obtain and maintain a TS/SCI

Desired Skills:

  • ML for either natural language processing, computer vision, reinforcement learning, generative modeling, or equivalent experience

  • PhD in data science, mathematics, statistics, computer science, a physical science or engineering is strongly desired

  • A mathematical background (Probability and Statistics)

  • An experienced grasp of version control using Git for nonlinear workflows

  • Thorough understanding of working in research, development and production environments

  • Background in image science, imagery exploitation, spatial analysis, and computer vision are a plus

  • R&D on remotely sensed data to include modeling and development of algorithms.

  • Ability to work independently or in a team environment

  • Strong technical writing and oral communication skills

  • Active Top Secret/SCI clearance

Radiance Technologies is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.