Urgent! Machine Learning Engineer, Foundation Model Job Opening In Seattle – Now Hiring Stripe
Who we are
About Stripe
Stripe’s mission is to accelerate global economic and technological development.
We offer financial infrastructure and a variety of services to serve the needs of a wide range of users, from startups to enterprises, with global scale and industry-leading reliability and product quality.
All financial services businesses face a trade-off between access, which we want to expand, and risk, which we want to minimize.
We use machine learning to scalably and intelligently optimize across both.
Machine learning is an integral part of almost every service at Stripe.
It is a key investment area with products and use cases that span merchant and transaction risk, payments optimization, identity, and merchant data analytics and insights.
We are also using the latest generative AI technologies (such as LLMs and FMs) to re-imagine product experiences and developing AI Assistants and Agents both for our customers (e.g. Radar Assistant and Sigma Assistant), and also to make Stripes more productive across Support, Marketing, Sales, and Engineering roles within the company.
About the team
We are dedicated to building and shipping the foundational AI and machine learning systems that will power our entire product suite.
Our mission is to fundamentally transform how Stripe uses ML, leveraging our extensive and rich dataset to solve some of the most challenging problems in payments and fraud.
We work closely with our partners in Risk, Payments, and Support to build transformative technologies that have a direct impact on our users.
From a data perspective, Stripe handles over per year, which is roughly .
We process petabytes of financial data using our ML platform to build features, train models, and deploy them to production.
We focus on seeing how LLMs can solve some of our hardest problems in merchant risk and understanding how we can align language to our immense ocean of payments data.
Some of our latest innovations have been around understanding how to best represent payments using transformers and enabling entirely new product ideas that are only made possible by GenAI.
What you'll do
As a Machine Learning Engineer on the Foundation Model team, you'll solve some of Stripe's most challenging technical problems that span multiple teams and directly impact our research and engineering efforts around building the Foundation Models that power our payments and risk solutions .
You'll be responsible for both hands-on technical contributions and driving strategic initiatives that shape how ML systems operate at scale across Stripe.
Responsibilities
Who you are
We're looking for someone who meets the minimum requirements to be considered for the role.
If you meet these requirements, you are encouraged to apply.
The preferred qualifications are a bonus, not a requirement.
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 10106 jobs in United States and 288 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, Foundation Model 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, Foundation Model 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, Foundation Model 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, Foundation Model 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.
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Here are some tips to help you prepare for and ace your job interview:
Before the Interview:To prepare for your Machine Learning Engineer, Foundation Model 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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