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Urgent! Machine Learning Engineer, Payments ML Accelerator Job Opening In Seattle – Now Hiring Stripe
About Stripe
Stripe is a financial infrastructure platform for businesses.
Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities.
Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead.
That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
About the team
The Payments ML Accelerator team is developing foundational ML capabilities that drive innovation across Stripe's payment products.
We build deep learning models that tackle Stripe's most complex payment challenges - from fraud detection to authorization optimization - and deliver measurable business impact.
Our work combines advanced ML techniques with large-scale data infrastructure to enable rapid experimentation and seamless deployment of AI-powered solutions.
As a central ML innovation hub, we work closely with product teams to identify high-impact opportunities and implement scalable solutions that can be leveraged across the organization.
What you'll do:
As a machine learning engineer on our team, you’ll develop advanced ML solutions that directly impact Stripe’s payment products and core business metrics.
Your role will span the entire ML lifecycle, from research and experimentation to production deployment.
You’ll work on high-leverage problems that require innovation in modeling, optimization, and system design.
Where possible, you’ll look beyond point solutions - designing approaches and architectures that are reusable, extensible, and serve as foundation models for future capabilities.
The role demands strong technical judgment, deep knowledge of modern ML methods, and the ability to translate ideas into systems that deliver measurable impact.
You’ll partner with product and engineering teams to identify opportunities where ML can move the needle today while setting Stripe up for long-term success.
Responsibilities:
Who you are:
We are looking for ML Engineers who are passionate about using ML to improve products and delight customers.
You have experience developing streaming feature pipelines, building ML models, and deploying them to production, even if it involves making substantial changes to backend code.
You are comfortable with ambiguity, love to take initiative, and have a bias towards action.
Minimum requirements
Preferred qualifications
Hybrid work at Stripe
This role is available either in an office or a remote location (35+ miles or 56+ km from a Stripe office).
In-office expectations
Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users.Working remotely at Stripe
A remote location is defined as being 35 miles (56 kilometers) or more from one of our offices.Pay and benefits
The annual US base salary range for this role is $212,000 - $318,000.
For sales roles, the range provided is the role’s On Target Earnings (OTE) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location.
Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.
Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.
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Unlock Your Machine Learning Potential: Insight & Career Growth Guide
Real-time Machine Learning Jobs Trends in Seattle, United States (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Machine Learning in Seattle, United States using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 11113 jobs in United States and 292 jobs in Seattle. This comprehensive analysis highlights market share and opportunities for professionals in Machine Learning roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Stripe is currently hiring and seeking a Machine Learning Engineer, Payments ML Accelerator to join their team. Feel free to download the job details.
Wait no longer! Are you also interested in exploring similar jobs? Search now: Machine Learning Engineer, Payments ML Accelerator Jobs Seattle.
An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Stripe adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a Machine Learning Engineer, Payments ML Accelerator Jobs United States varies, but the pay scale is rated "Standard" in Seattle. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for Machine Learning Engineer, Payments ML Accelerator typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
To improve your chances of getting hired for Machine Learning Engineer, Payments ML Accelerator, consider enhancing your skills. Check your CV/Résumé Score with our free Resume Scoring Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.
Here are some tips to help you prepare for and ace your job interview:
Before the Interview:To prepare for your Machine Learning Engineer, Payments ML Accelerator interview at Stripe, research the company, understand the job requirements, and practice common interview questions.
Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Stripe's products or services and be prepared to discuss how you can contribute to their success.
By following these tips, you can increase your chances of making a positive impression and landing the job!
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