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Full Time Machine Learning Finance Jobs (NOW HIRING)

Jane Street

Machine Learning Researcher

New York, NY · On-site

You'll spend the bulk of your internship working closely with full-time machine learning ... About You If you've never thought about a career in finance, you're in good company. Many of us ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

You'll spend the bulk of your internship working closely with full-time machine learning ... About You If you've never thought about a career in finance, you're in good company. Many of us ...

Strivector Corp

Machine Learning

Manhattan, NY · On-site

They are seeking a Machine Learning professional capable of tackling research problems with commercial applications, applying technical expertise to real-world financial and operational challenges.

Jane Street

Machine Learning Engineer

New York, NY · On-site

You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ... About You If you've never thought about a career in finance, you're in good company. Many of us ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ... About You If you've never thought about a career in finance, you're in good company. Many of us ...

Tennant Company

Machine Learning Engineer

Golden Valley, MN · On-site

$119K - $122K/yr

Tennant Company seeks a full-time Machine Learning Engineer based in Golden Valley, MN. Responsible for utilizing experience in emerging technologies such as Cloud computing, Big Data, Deep Machine ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

About Poesis Whoever builds the leading intelligence for finance will create far more than returns ... full-time employees. Working at Poesis As an early team member, you'll help shape not just the ...

Apple

Sr. Machine Learning Engineer - Finance

Austin, TX

$184K - $277K/yr

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 ...

Paylocity

Machine Learning Engineer

Job Type Full-time Description Paylocity is an award-winning provider of cloud-based HR and payroll ... your finances. And if it's career development you desire, we provide that, too! At Paylocity ...

Apple

Sr. Machine Learning Engineer - Finance

Austin, TX

$184K - $277K/yr

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 ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

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Full Time Machine Learning Finance information

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$25K

$92.6K

$135.5K

How much do full time machine learning finance jobs pay per year?

As of Aug 21, 2026, the average yearly pay for full time 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 full time machine learning finance professional?

A Full Time Machine Learning Finance job involves applying machine learning techniques and algorithms to financial data and problems. Professionals in this role develop predictive models for tasks such as risk assessment, trading strategies, fraud detection, and portfolio optimization. They work closely with financial analysts and data scientists to create solutions that can automate processes, improve decision-making, and identify patterns in large datasets. The role typically requires strong knowledge of both finance and advanced machine learning methods, as well as programming and data analysis skills.

What are the key skills and qualifications needed to thrive as a full time machine learning finance professional?

To thrive as a Full Time Machine Learning Finance professional, you need a solid background in quantitative analysis, statistics, computer science, and finance, usually supported by a relevant degree. Proficiency with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with financial data systems are essential. Strong problem-solving abilities, attention to detail, and effective communication skills help you stand out in this field. These skills ensure the successful development and deployment of data-driven financial models that support better decision-making and risk management.

What are some common challenges faced by machine learning professionals working in the finance sector?

Machine learning professionals in finance often encounter challenges such as dealing with sensitive and highly regulated data, ensuring model transparency and explainability for compliance purposes, and adapting to rapidly changing market conditions. Additionally, integrating machine learning models with existing financial systems and collaborating closely with domain experts, such as quantitative analysts and risk managers, are key parts of the role. Staying updated on both technological advancements and regulatory changes is also essential for success in this dynamic environment.

What is the difference between Full Time Machine Learning Finance vs Full Time Data Scientist?

AspectFull Time Machine Learning FinanceFull Time Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of finance and machine learning certificationsDegree in Statistics, Computer Science, or related fields; data analysis and programming skills
Work EnvironmentFinancial institutions, hedge funds, banks, fintech companiesTech companies, consulting firms, finance, healthcare, retail
Industry UsageFinance-specific applications like risk modeling, algorithmic tradingBroad industry applications including marketing, healthcare, finance

Full Time Machine Learning Finance roles focus on applying machine learning techniques specifically to financial data and problems within financial institutions. In contrast, Full Time Data Scientist positions have a broader scope across various industries, utilizing data analysis and modeling skills to solve diverse business challenges. While both roles require strong technical skills, the finance-specific role emphasizes financial knowledge and applications.

Can full time machine learning finance be used in finance?

Full-time machine learning finance roles involve applying machine learning techniques to financial data for tasks such as risk assessment, trading algorithms, and fraud detection. These positions require skills in data analysis, programming, and financial modeling, and are commonly found in investment firms, banks, and fintech companies.
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The most popular types of Machine Learning Finance jobs are:

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Full Time Machine Learning Finance jobs near you
Infographic showing various Full Time Machine Learning Finance 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 $92,631 per year, or $44.5 per hour.

Machine Learning Researcher

Jane Street

New York, NY • On-site

Full-time

Re-posted 8 days ago

Job description

About the Position
Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Researcher while also providing a truly unparalleled educational experience. You'll work side by side with experienced ML Researchers on projects that we've selected for their combination of novel ML ideas and relevance to real-world systematic trading strategies. You'll learn how we think about markets through challenging classes and activities, and practice using established methods alongside our own unique twists to train practical models.
At Jane Street, the lines between research, technology, and trading are intentionally blurry, and you'll have access to petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing thousands of high-end GPUs. Trading poses unusual challenges-large models and nonstationary datasets in a competitive multi-agent environment-that force us to search for novel techniques.
You'll spend the bulk of your internship working closely with full-time machine learning researchers on projects drawn from their own work. You might conduct an end-to-end study of an unexplored dataset, try a new modeling paradigm for a thorny problem, or consider blue-sky approaches that we're still trying to figure out. The problems we work on rarely have clean, definitive answers, and they often require insights from colleagues across the firm with different areas of expertise. Depending on the day, you might be diving deep into market data, tuning hyperparameters, debugging training issues, or analyzing the predictions your model makes.
Note that given the IP-sensitive nature of machine learning research at Jane Street, it is unlikely that any research findings associated with the internship will be suitable for outside academic publication.
About You
If you've never thought about a career in finance, you're in good company. Many of us were in the same position before working here. If you have a curious mind and a passion for solving interesting problems, we have a feeling you'll fit right in. We're more interested in how you think and learn than what you currently know. You should be:
  • An undergraduate, PhD student, or postdoc with practical experience working on ML problems
  • Interested in applying logical and mathematical thinking to all kinds of problems
  • Curious about the machine learning landscape and excited to apply state-of-the-art techniques drawn from many problem domains
  • Fluent with a versatile set of models and tricks
  • Able to rapidly implement and iterate on your ideas in Python and your favorite ML framework
  • Eager to ask questions, admit mistakes, and learn new things

If you'd like to learn more, you can read about our interview process and meet some of the team. Learn more about Jane Street's internship program here.

Apply