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Remote Machine Learning Finance Jobs (NOW HIRING)

Hang

Machine Learning Engineer

New York, NY · On-site +1

Hang draws from years of deep expertise in loyalty, game design, and finance with employees from ... This person will implement and develop machine learning models to enhance our platform ...

Focus Financial Partners

Machine Learning Engineer

$160K - $180K/yr

We are seeking a skilled Machine Learning Engineer with approximately three years of hands-on ... Focus is a leading financial services firm comprised of integrated wealth management, family office ...

Focus Financial Partners

Machine Learning Engineer

$160K - $180K/yr

We are seeking a skilled Machine Learning Engineer with approximately three years of hands-on ... Focus is a leading financial services firm comprised of integrated wealth management, family office ...

Apex Informatics

Machine Learning Engineer

Remote We are seeking an Applied Machine Learning Engineer with a strong focus on practical solutions and software development (ability to work on both open-ended research problems and production ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

Paylocity

Senior Machine Learning Engineer

$125K - $165K/yr

... your finances. And if it's career development you desire, we provide that, too! At Paylocity ... This is a fully remote position, allowing you to work from home or location of record within the U.

Paylocity

Staff Machine Learning Engineer

... your finances. And if it's career development you desire, we provide that, too! At Paylocity ... This is a fully remote position, allowing you to work from home or location of record within the U.

Workiva

$40/hr

This internship is primarily a remote opportunity. However, if you are located near one of our ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

This internship is primarily a remote opportunity. However, if you are located near one of our ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

This internship is primarily a remote opportunity. However, if you are located near one of our ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

This internship is primarily a remote opportunity. However, if you are located near one of our ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

This internship is primarily a remote opportunity. However, if you are located near one of our ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

This internship is primarily a remote opportunity. However, if you are located near one of our ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

This internship is primarily a remote opportunity. However, if you are located near one of our ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

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Remote Machine Learning Finance information

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$25K

$92.6K

$135.5K

How much do remote machine learning finance jobs pay per year?

As of Sep 12, 2026, the average yearly pay for remote 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 remote machine learning finance professional?

A Remote Machine Learning Finance job involves applying machine learning techniques and algorithms to financial data and problems, often from a remote location. Professionals in this field develop models to predict market trends, assess risks, automate trading, or detect fraud using large datasets. Remote roles allow employees to work from anywhere, collaborating with teams virtually and using cloud-based tools to analyze data. These positions typically require strong programming skills, knowledge of finance, and experience with machine learning frameworks.

How do remote machine learning finance professionals typically collaborate with cross-functional teams?

Remote machine learning professionals in finance often work closely with data analysts, financial experts, and software engineers to develop and deploy predictive models. Collaboration is typically facilitated through virtual meetings, shared documentation, and project management tools. Clear communication and regular check-ins are crucial for aligning goals and ensuring that machine learning solutions address real business needs. Many organizations also encourage participation in virtual workshops and code reviews to maintain a strong sense of teamwork despite the remote setting.

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

To excel in Remote Machine Learning Finance, strong analytical skills, a solid background in statistics or mathematics, and experience with financial data are essential, often supported by a degree in computer science, finance, or a related field. Familiarity with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or Scikit-learn), and knowledge of financial modeling tools are typically required. Excellent problem-solving, communication, and the ability to work independently are standout soft skills in this remote environment. These abilities are crucial for developing effective financial models, interpreting complex data, and collaborating with distributed teams to drive business value.
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Remote Machine Learning Finance jobs near you
Infographic showing various Remote Machine Learning Finance job openings in the United States as of September 2026, with employment types broken down into 43% Full Time, and 57% Contract. Highlights an 100% Remote job distribution, with an average salary of $92,631 per year, or $44.5 per hour.

Machine Learning Engineer

San Francisco, CA • On-site, Remote

Swish Analytics
Spectator Sports • 1 - 10 employees
Learn more about Swish Analyticsexternal

$160K/yr

Full-time

Re-posted 26 days ago

Job description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and enterprise clients.
The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to "roll your own" and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.
This position is 100% remote
Responsibilities:
  • Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.
  • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.
  • Build, test, deploy and maintain production systems.
  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.
  • Support maintenance and optimization of cloud-native EDW and ETL solutions.
  • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Use extensive experience to build, test, debug, and deploy production-grade components.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Participate in development of database structures that fit into the overall architecture of Swish systems

Qualifications:
  • Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area
  • 5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs
  • A proven background in quantitative analytics, trading, or engineering is required for this position
  • Demonstrated experience developing data science modeling systems and infrastructure at scale
  • Experience with Python and exposure to modern machine learning frameworks
  • Proficient in SQL; experience with MySQL
  • Background and/or interest in Rust preferred
  • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback
  • Strong communication skills when discussing technical concepts with technical and non-technical colleagues

Base salary: starting at $160,000 base plus bonus potential
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Engineering & Infrastructure Role Data Science Infrastructure Locations San Francisco, CA - Remote Remote status Fully Remote

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