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Machine Learning Finance Jobs (NOW HIRING)

Stefanini

Machine Learning Engineer

Allen Park, MI · On-site

Stefanini is looking for a Machine Learning Engineer(Allen Park, MI) For quick apply, please reach ... markets, including financial services, manufacturing, telecommunications, chemical services ...

Robinhood

Machine Learning Engineer

Bellevue, WA · On-site

... world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers ... We're looking for an exceptional Machine Learning Engineer to help shape the future of our core ...

Somatus, Inc.

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and technology teams to help clinical, operational, and financial partners solve advanced analytical problems.

Booz Allen Hamilton

Machine Learning Engineer

Aurora, CO · On-site

$77K - $176K/yr

Job Number: R0246351 Machine Learning Engineer The Opportunity: As a programmer, you know that ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Booz Allen Hamilton

Machine Learning Engineer

Aurora, CO

$77K - $176K/yr

Machine Learning Engineer The Opportunity: As a programmer, you know that machine learning is ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

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 ...

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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 Sep 3, 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 is a machine learning finance?

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.

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 are the key skills and qualifications needed to thrive in machine learning finance, 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.

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What are the most commonly searched types of Machine Learning Finance jobs?

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Machine Learning Finance jobs near you
Infographic showing various Machine Learning Finance job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, and 10% Contract. Highlights an 90% In-person, and 10% Remote job distribution, with an average salary of $92,631 per year, or $44.5 per hour.

Sr. Machine Learning Engineer - Finance

Apple

Austin, TX • On-site

Full-time

Re-posted 18 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 680 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and curiosity to your job and there's no telling what you could accomplish. Do you love thinking analytically? Just as our customers find value in Apple products, the Finance group finds value for both Apple and its shareholders.
As a machine learning engineer in Finance, you'll play an integral and global role in building the data foundations, services, and platforms used for delivering insights and automating decisions for Apple's Finance organization.
Description
This role will require you to be collaborative by learning intra-team and business process in order to build infrastructure and services to enable an effective Machine Learning practice. You will help lead the charge by developing a strong ML Ops process in a dynamic Finance environment where you will deal with unique challenges specific to Finance organizations, such as SOX and regulatory compliance. Your ability to instill and proliferate strong software engineering practices into team data science and machine learning processes will be critical.
Minimum Qualifications
Undergraduate degree (computer science, data science, finance, economics, accounting, or related business discipline) with seven years demonstrated experience
Experience building data models and scalable pipelines using SQL and big data technologies, with expertise in data ops best practices
Experience developing in Python while following DRY principles, modularity, and testing standards, with version control, code review.
Experience applying ML algorithms for regression, classification, and anomaly detection; build generative AI and agentic solutions; implement MLOps/LLMOps including CI/CD, drift monitoring, and cloud platforms (AWS, GCP, Azure)
Ability to explain technical details to non-technical audiences
Understands and advocates version control, test driven development and strong CI/CD process
Preferred Qualifications
Graduate degree (computer science, data science, math, quantitative finance, or similar discipline) with five years experience
Previous experience working in a corporate finance, accounting, or supply chain organization
Understanding of or ability to learn financial statements, P&L impact, high level accounting principles, SOX and tax compliance and month-end close process
Experience with front end (.js experience)

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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