Know ATS Score
CV/Résumé Score
  • Expertini Resume Scoring: Our Semantic Matching Algorithm evaluates your CV/Résumé before you apply for this job role: Machine Learning Engineer, Payments ML Accelerator.
United States Jobs Expertini

Urgent! Machine Learning Engineer, Payments ML Accelerator Job Opening In Seattle – Now Hiring Stripe

Machine Learning Engineer, Payments ML Accelerator



Job description

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:

  • Design and deploy deep learning architectures and foundation models to address problems across key payment entities such as merchants, issuers, or customers
  • Identify high-impact opportunities, and drive the long-term ML roadmap through well-scoped high-leverage initiatives
  • Architect generalizable ML workflows to enable rapid scaling and optimized online performance
  • Deploy ML models online and ensure operational stability
  • Experiment with advanced ML solutions in the industry and ideate on product applications 
  • Explore cutting-edge ML techniques and evaluate their potential to solve business problems
  • Work closely with ML infrastructure teams to shape new platform capabilities
  • 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

  • Minimum 7 years of industry experience doing end-to-end ML development on a machine learning team and bringing ML models to production 
  • Proficient in Python, Scala, and Spark
  • Proficient in deep learning and LLM/foundation models
  • Preferred qualifications

  • MS/PhD degree in quantitative field or ML/AI (e.g. computer science, math, physics, statistics)
  • Knowledge about how to manipulate data to perform analysis, including querying data, defining metrics, or slicing and dicing data to evaluate a hypothesis
  • Experience evaluating niche and upcoming ML solutions
  • 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.

    This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.

    Working remotely at Stripe

    A remote location is defined as being 35 miles (56 kilometers) or more from one of our offices.

    While you would be welcome to come into the office for team/business meetings, on-sites, meet-ups, and events, our expectation is you would regularly work from home rather than a Stripe office.

    Stripe does not cover the cost of relocating to a remote location.

    We encourage you to apply for roles that match the location where you currently live or plan to live.

    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.


    Required Skill Profession

    Computer Occupations



    Your Complete Job Search Toolkit

    ✨ Smart • Intelligent • Private • Secure

    Start Using Our Tools

    Join thousands of professionals who've advanced their careers with our platform

    Rate or Report This Job
    If you feel this job is inaccurate or spam kindly report to us using below form.
    Please Note: This is NOT a job application form.


      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.

    • Are You Looking for Machine Learning Engineer, Payments ML Accelerator Job?

      Great news! 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: .

    • The Work Culture

      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:
      • 1. Independence
      • 2. Loyalty
      • 3. Impartiality
      • 4. Integrity
      • 5. Accountability
      • 6. Respect for human rights
      • 7. Obeying United States laws and regulations
    • What Is the Average Salary Range for Machine Learning Engineer, Payments ML Accelerator Positions?

      The average salary range for a 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.

    • What Are the Key Qualifications for Machine Learning Engineer, Payments ML Accelerator?

      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.

    • How Can I Improve My Chances of Getting Hired for Machine Learning Engineer, Payments ML Accelerator?

      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 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.

    • Interview Tips for Machine Learning Engineer, Payments ML Accelerator Job Success
      Stripe interview tips for Machine Learning Engineer, Payments ML Accelerator

      Here are some tips to help you prepare for and ace your job interview:

      Before the Interview:
      • Research: Learn about the Stripe's mission, values, products, and the specific job requirements and get further information about
      • Other Openings
      • Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.
      • Dress Professionally: Choose attire appropriate for the company culture.
      • Prepare Questions: Show your interest by having thoughtful questions for the interviewer.
      • Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.
      During the Interview:
      • Be Punctual: Arrive on time to demonstrate professionalism and respect.
      • Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.
      • Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.
      • Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.
      • Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.
      • Follow Up: Send a thank-you email to the interviewer within 24 hours.
      Additional Tips:
      • Be Yourself: Let your personality shine through while maintaining professionalism.
      • Be Honest: Don't exaggerate your skills or experience.
      • Be Positive: Focus on your strengths and accomplishments.
      • Body Language: Maintain good posture, avoid fidgeting, and make eye contact.
      • Turn Off Phone: Avoid distractions during the interview.
      Final Thought:

      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!

    • How to Set Up Job Alerts for Machine Learning Engineer, Payments ML Accelerator Positions

      Setting up job alerts for Machine Learning Engineer, Payments ML Accelerator is easy with United States Jobs Expertini. Simply visit our job alerts page here, enter your preferred job title and location, and choose how often you want to receive notifications. You'll get the latest job openings sent directly to your email for FREE!