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Machine Learning Finance Jobs (NOW HIRING)

Q2 Software, Inc.

Machine Learning Engineer

Cary, NC · On-site

Our solutions allow financial institutions to focus more of their time and energy on their mission: serving their customers and communities. As a Machine Learning Engineer, you will help build and ...

Q2

Machine Learning Engineer

Cary, NC · On-site

Our solutions allow financial institutions to focus more of their time and energy on their mission: serving their customers and communities. As a Machine Learning Engineer, you will help build and ...

Visa

Director, Machine Learning

Austin, TX · On-site

... financial institutions and government entities across more than 200 countries and territories ... We are currently looking for a Director of Machine Learning who will take the lead and manage ...

Jane Street

Machine Learning Engineer

Manhattan, NY

Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading ... If you've never thought about a career in finance, you're in good company. Many of us were in the ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading ... If you've never thought about a career in finance, you're in good company. Many of us were in the ...

Visa

Director, Machine Learning

Austin, TX · Hybrid

... financial institutions and government entities across more than 200 countries and territories ... We are currently looking for a Director of Machine Learning who will take the lead and manage ...

Virtu Financial

Machine Learning Researcher

New York, NY

$200K - $300K/yr

As a Machine Learning Researcher at Virtu, you'll pursue high-impact research opportunities within ... Adapt techniques from your area of expertise to achieve breakthrough results in the financial ...

Virtu Financial

Machine Learning Researcher

New York, NY · On-site

$200K - $300K/yr

As a Machine Learning Researcher at Virtu, you'll pursue high-impact research opportunities within ... Adapt techniques from your area of expertise to achieve breakthrough results in the financial ...

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a ... Build and maintain data pipelines that move financial data from storage into training workflows ...

Virtu Financial

Machine Learning Engineer

New York, NY

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a ... Build and maintain data pipelines that move financial data from storage into training workflows ...

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Machine Learning Finance information

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$25K

$92.6K

$135.5K

How much do machine learning finance jobs pay per year?

As of Jun 13, 2026, the average yearly pay for machine learning finance in the United States is $92,631.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $109,000.00 per year, depending on experience, location, and employer.

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

To excel in Machine Learning Finance, you need strong quantitative skills, proficiency in programming (typically Python or R), and a solid background in both finance and machine learning, often supported by a relevant degree such as in computer science, statistics, mathematics, or finance. Familiarity with machine learning libraries (like TensorFlow, scikit-learn), financial modeling tools, and certifications such as CFA or FRM can be highly beneficial. Excellent problem-solving abilities, communication skills, and a collaborative attitude help professionals translate complex data into practical financial insights and work effectively with both technical and non-technical stakeholders. These competencies enable you to create robust predictive models, drive innovation in financial analysis, and ensure sound decision-making in dynamic industry settings.

What are some typical challenges faced by professionals in Machine Learning Finance roles?

Professionals in Machine Learning Finance often encounter challenges such as working with noisy or incomplete financial data, keeping up with rapidly evolving algorithms, and ensuring model compliance with industry regulations. They may also need to bridge the gap between technical model development and practical business needs, communicating complex findings to non-technical teams. These roles typically involve close collaboration with traders, financial analysts, and risk managers to ensure that machine learning solutions are both accurate and actionable. Facing these challenges can be rewarding, offering significant opportunities for skill development and career advancement in a data-driven financial landscape.

What is a Machine Learning Finance job?

A Machine Learning Finance job involves applying machine learning techniques to financial problems such as risk assessment, algorithmic trading, fraud detection, and portfolio optimization. Professionals in this field build predictive models, analyze large datasets, and automate decision-making processes to improve financial performance. They typically work with tools like Python, TensorFlow, and financial datasets to develop AI-driven solutions. These roles require expertise in machine learning, statistics, and financial markets, often blending data science with quantitative finance.

More about Machine Learning Finance jobs
What cities are hiring for Machine Learning Finance jobs? Cities with the most Machine Learning Finance job openings:
What are the most commonly searched types of Machine Learning Finance jobs? The most popular types of Machine Learning Finance jobs are:
What states have the most Machine Learning Finance jobs? States with the most job openings for Machine Learning Finance jobs include:
What job categories do people searching Machine Learning Finance jobs look for? The top searched job categories for Machine Learning Finance jobs are:
Machine Learning Finance jobs near you
Infographic showing various Machine Learning Finance job openings in the United States as of June 2026, with employment types broken down into 48% Full Time, 50% Part Time, 1% Temporary, and 1% Contract. Highlights an 81% Physical, 8% Hybrid, and 11% Remote job distribution, with an average salary of $92,631 per year, or $44.5 per hour.

Machine Learning Engineer

Q2 Software, Inc.

Cary, NC • On-site

Other

Medical

This job post has expired today. Applications are no longer accepted.

Job description

As passionate about our people as we are about our mission.
Why Join Q2?
Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs in the U.S. and internationally. Our mission is simple: build strong and diverse communities through innovative financial technology-and we do that by empowering our people to help create success for our customers.
What Makes Q2 Special?
Being as passionate about our people as we are about our mission. We celebrate our employees in many ways, including our "Circle of Awesomeness" award ceremony and day of employee celebration among others! We invest in the growth and development of our team members through ongoing learning opportunities, mentorship programs, internal mobility, and meaningful leadership relationships. We also know that nothing builds trust and collaboration like having fun. We hold an annual Dodgeball for Charity event at our Q2 Stadium in Austin, inviting other local companies to play, and community organizations we support to raise money and awareness together.
The Risk & Fraud team at Q2 helps our customers take a proactive stance against fraud while managing the risks inherent to their business. We build and enhance products that evolve with the ever-changing fraud landscape, delivering tangible value to our customers. Our solutions allow financial institutions to focus more of their time and energy on their mission: serving their customers and communities.
As a Machine Learning Engineer, you will help build and operate production systems that power our fraud products. You'll work closely with data scientists and engineers to bring models into production ensuring they are reliable, scalable, and maintainable.
You'll gain hands-on experience working across model development, evaluation, deployment, and ongoing monitoring and improvements. This is an applied role - the software you build will be solving real problems for real customers, and will therefore need to be testable, reliable, and production-ready.
A Typical Day:
Your Key Responsibilities
  • Build and maintain systems and pipelines that support training, evaluation, and inference for machine learning models.
  • Contribute to deploying machine learning models into production environments and ensuring they run reliably at scale.
  • Write clean, maintainable, and well-tested code following production engineering best practices.
  • Support monitoring and troubleshooting production ML systems, including data pipelines and model performance.
  • Collaborate with data scientists and engineers to productionalize models and integrate them into scalable applications.
  • Help improve the reliability, scalability, and performance of ML systems over time.
  • Contribute to improving tooling and infrastructure that supports the ML development lifecycle.
You are more likely to excel in the role if you:
  • Enjoy autonomy in your work and feel a sense of ownership in the team's goals. You
    work quickly but with the big picture in mind.
  • Have empathy for the end user and a desire to measure your work by both the
    customer value and technical quality.
  • Have enthusiasm for the field and professional development.
Bring Your Passion, Do What You Love. Here's What We're Looking For:
Must Haves
  • Typically requires a Bachelor's degree in a relevant field and a minimum of 2+ years of related experience; or an advanced degree; or equivalent related work experience.
  • Proficiency in Python.
  • Experience writing clean, maintainable code and using version control (e.g., Git).
  • Experience with machine learning and common frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Nice to Have
  • Experience building end-to-end ML systems, including data pipelines, model training, deployment and monitoring.
  • Experience deploying or integrating machine learning models into applications.
  • Experience building APIs, backend services, or working with distributed systems.
  • Familiarity with cloud platforms (AWS, GCP, or Azure).
  • Exposure to MLOps concepts such as CI/CD and model monitoring.
  • Experience working with large datasets or data processing frameworks.
  • Experience with other programming languages (e.g. Typescript).
This position requires fluent written and oral communication in English.
Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
Health & Wellness
  • Hybrid Work Opportunities
  • Flexible Time Off
  • Career Development & Mentoring Programs
  • Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave for eligible new parents
  • Community Volunteering & Company Philanthropy Programs
  • Employee Peer Recognition Programs - "You Earned it"

Click here to find out more about the benefits we offer.
Our Culture & Commitment:
We're proud to foster a supportive, inclusive environment where career growth, collaboration, and wellness are prioritized. And our benefits go beyond healthcare-offering resources for physical, mental, and professional well-being. Click here to find out more about the benefits we offer. Q2 employees are encouraged to give back through volunteer work and nonprofit support through our Spark Program (see more). We believe in making an impact-in the industry and in the community.
We are 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, age, disability, genetic information, or veteran status.
Applicants in California or Washington State may not be exempt from federal and state overtime requirements

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