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Remote Machine Learning Finance Jobs (NOW HIRING)

Required: * 6+ years of work experience building and deploying machine learning systems into ... Generous, flexible paid time off policy. * 401(k) with Financial Guidance from Morgan Stanley.

This role is fully remote within the US** What You'll Do * Build and scale machine-learning driven features across multiple products * Design reusable architecture that powers and accelerates machine ...

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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 May 31, 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 are the key skills and qualifications needed to thrive as a Remote Machine Learning Finance professional, and why are they important?

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.

How do remote machine learning professionals in finance 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 is a Remote Machine Learning Finance job?

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.
More about Remote Machine Learning Finance jobs
What cities are hiring for Remote Machine Learning Finance jobs? Cities with the most Remote 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 Remote Machine Learning Finance jobs? States with the most job openings for Remote Machine Learning Finance jobs include:
Infographic showing various Remote Machine Learning Finance job openings in the United States as of May 2026, with employment types broken down into 40% Internship, 20% Full Time, 20% Part Time, and 20% Contract. Highlights an 100% Remote job distribution, with an average salary of $92,631 per year, or $44.5 per hour.
Remote Senior Applied Machine Learning Engineer - Applied Machine Learning Team

Remote Senior Applied Machine Learning Engineer - Applied Machine Learning Team

Redfin Corporation

Seattle, WA • On-site, Remote

$139.40K - $183.80K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 25 days ago


Redfin rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

2nd of 153 rated real estate companies


Job description

This posting will be open until June 30, 2026. Applications received after this date may not be considered.
Hybrid from Seattle is the preferred location but this role is open to fully remote candidates.
The Applied Machine Learning group at Redfin works towards redefining real estate in the customer's favor using machine learning. We work on foundational problems in the real estate space including recommendations ("Where should I live?") and price estimation ("How much is a home worth?"). The Brokerage Recommendations product alone, which we power drives 27% of all traffic to Redfin platforms. We have real estate data at a national level and work across various domains in machine learning using large-scale multi-modal property data (documents, images, text, video, 3D scans etc.). Our team also owns and maintains end-to-end production-grade large-scale machine learning infrastructure and systems serving hundreds of millions of consumers.
As a Senior Machine Learning Engineer for the Applied Machine Learning Team, you'll breathe life into our research by transforming prototypes into high-performance production systems, building the automated MLOps pipelines and real-time optimizations that keep our models running at scale. As the strategic bridge between research and engineering, you'll own the health of our valuation and recommender systems to ensure they remain fast, reliable, and impactful for millions of users.
About the Role
  • You will productionize models by converting research-grade code into performant, clean, and maintainable production systems.
  • You will implement MLOps best practices, including CI/CD for machine learning, automated retraining pipelines, and robust model versioning.
  • You will optimize models for inference to ensure high-speed performance and efficiency in real-time environments.
  • You will monitor models in production, proactively identifying and mitigating issues related to data drift, concept drift, and system latency.
  • You will co-create the next generation of data-driven insights for automated valuation models (AVM) and recommender systems.
  • You will identify and implement iterative improvements to the machine learning models that power production-scale, customer-facing experiences.
  • You will serve as a technical bridge, assisting other engineers and stakeholders in understanding and applying data science methodologies and findings across the organization.
  • You will build data products and analytical tools that drive critical business metrics and revenue growth, directly impacting the home buying and selling experience.

About You
  • You have 5+ years of software engineering experience, with at least 2 years specifically focused on deploying and scaling machine learning models in production environments.
  • You are highly proficient in Python and capable of writing production-grade, modular code.
  • You possess a deep understanding of the end-to-end ML lifecycle, including training versus inference workflows, feature stores, and model versioning.
  • You are competent with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn. While you may not be building architectures from scratch, you can effectively debug, tune, and optimize models for inference.
  • You are competent with monitoring, observability, and production maintenance. You can effectively set up and manage logging, metrics, and alerting pipelines, debug production issues, and ensure system reliability and performance in high-scale feature storeYou have hands-on experience with Docker and Kubernetes. You understand how to deploy, manage, and scale containers within a cluster environment.
  • You have experience implementing model monitoring and operational rigor, including tracking data drift and latency, as well as utilizing A/B testing frameworks to validate model performance in the wild.
  • You are proficient in SQL and familiar with distributed data processing tools like Spark or Kafka to ensure that data reaching the model is high-quality and consistent with training distributions.

What you'll get
Our team members fuel our strategy, innovation and growth, so we ensure the health and well-being of not just you, but your family, too! We go above and beyond to give you the support you need on an individual level and offer all sorts of ways to help you live your best life. We are proud to offer eligible team members perks and health benefits that will help you have peace of mind. Simply put: We've got your back. Check out our full list of Benefits and Perks.
About us
Redfin is revolutionizing the $75 billion real estate industry. We use data, beautiful software, and innovative design to put customers first at every step in the home-buying and selling process. Get ready to dive headfirst into our award-winning website and mobile apps, solving complex business problems in a highly visible, customer-centric way. If you value doing great work in a collaborative environment, join our team!
This job description is an outline of the primary responsibilities of this position and may be modified at the discretion of the company at any time. Decisions related to employment are not based on race, color, religion, national origin, sex, physical or mental disability, sexual orientation, gender identity or expression, age, military or veteran status or any other characteristic protected by state or federal law. The company provides reasonable accommodations to qualified individuals with disabilities in accordance with applicable state and federal laws. Applicants requiring reasonable accommodations in completing the application and/or participating in the application process should contact a member of the Human Resources team, at Careers@Rocket.com.
The compensation information below is provided in compliance with all applicable job posting disclosure requirements. The compensation for this position is $164,300.00$258,100.00. The position may also be eligible for an annual bonus, incentives, and other employment-related benefits including, but not limited to, medical, dental, and vision benefits, 401K retirement plan, and paid-time off. More information regarding these benefits and others can be found here. The information regarding compensation and other benefits included in this paragraph is the company's current, good faith estimate at the time of posting. [Compensation and benefits are subject to modification from time to time as the Company, in its sole and exclusive discretion, deems appropriate.] The Company may determine during its future reviews of the proposed compensation and benefits provided for this position, that the compensation and benefits for such position should be reduced. In no event will the Company reduce the compensation for the position to a level below the applicable jurisdictional minimum wage rate for the position. Los Angeles County and San Francisco Candidates only: qualified applicants with arrest or conviction records will be considered for employment per the Fair Chance Ordinance and the Fair Chance Initiative for Hiring.