Search jobs > South San Francisco, CA > Machine learning engineer

Machine Learning Engineer, Payment Intelligence

Stripe
South San Francisco
$173.1K-$316.8K a year
Full-time

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 Payment Intelligence ML organization optimizes each of the billions of dollars of transactions processed by Stripe annually on behalf of our customers, maximizing successful transactions while minimizing payment costs and fraud.

We leverage ML to serve real-time predictions as part of Stripe’s payment infrastructure and risk controls. We own products like , , and end-to-end, operating lightning fast world-scale services and cutting-edge ML models.

What you’ll do

We are looking for Machine Learning Engineers to own the end-to-end lifecycle of applied ML model development and deployment in service of consumer facing products like , , and .

You will work closely with software engineers, machine learning engineers (MLE), data scientists (DS), and ML platform infrastructure teams to design, build, deploy, and operate Stripe’s ML-powered payment decisioning systems, including improving existing ML models and developing new ML solutions.

Responsibilities

  • Design and deploy new models using tools (such as Spark, Presto, XGBoost, Tensorflow, PyTorch) and iteratively improve verification and fraud models to protect millions of users from fraud
  • Envision and develop new models for fraud detection i.e work with large payment datasets to find creative new methods of detecting and deterring fraudulent behavior.
  • Propose new feature ideas and design real-time data pipelines to incorporate them into our models.
  • Integrate new signals into ML pipelines, derive new ML features, and build workflows to make this process fast
  • Integrate new models and behaviors into Stripe’s core payment flow
  • Collaborate and execute projects cross-functionally with the data science, product management, infrastructure, and risk teams
  • Ensure engineering outcomes meet or exceed established standards of excellence in code quality, system design, and scalability
  • Mentor engineers earlier in their technical careers to help them grow
  • Propose and implement innovative product ideas to reduce costs and combat fraud at Stripe

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

  • Over 3+ years industry experience building machine learning applications in large scale distributed systems.
  • 2+ year of experience working within a team responsible for developing, managing, and optimizing ML models or ML infrastructure
  • Experience designing and training machine learning models to solve critical business problems
  • Experience performing analysis, including querying data, defining metrics, or slicing and dicing data to model performance and business metrics

Preferred qualifications

  • An advanced degree in a quantitative field (e.g. stats, physics, computer science)
  • Proven track record of building and deploying machine learning systems that have effectively solved critical business problems
  • Experience in adversarial domains like Payments, Fraud, Trust, or Safety
  • Experience working in Python, Java and / or Ruby codebases
  • Experience in software engineering in a production environment.

Hybrid work at Stripe

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.

Pay and benefits

The annual US base salary range for this role is $173,100 - $316,800. 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.

30+ days ago
Related jobs
Promoted
Pinterest
San Francisco, California

D degree in Computer Science, Machine learning, Statistics, or related field. We leverage a wide range of ML technologies, such as LLM, multi-modal learning, distillation, etc to that end. Serve as technical authority for engineering design and implementation of end to end systems to develop ads con...

Promoted
Apple
San Francisco, California

As a Machine Learning Engineer, you will play a crucial role in designing, developing, and implementing machine learning algorithms to power this feature. As a Machine Learning Engineer, you will be responsible for developing and applying machine learning techniques to improve Siri's ability to unde...

Promoted
Pinterest
Palo Alto, California

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pin...

Apple
San Francisco, California

Do you want to make Siri and Apple products smarter for our users? The Information Intelligence teams are building groundbreaking technology for algorithmic search, machine learning, natural language processing, and artificial intelligence. Join us as a Cloud Infrastructure Engineer, collaborating a...

Attentive
San Francisco, California

You have proficiency or experience with PythonYou have extensive experience using machine learning and data analysis, or similar, to build scalable systems and data-driven products, working with cross-functional teams. You have led cross-functional machine learning projects across teams. Our fronten...

Unreal Gigs
San Francisco, California

Promote a culture of continuous learning and experimentation, staying abreast of advancements in AI, machine learning, and space technology. Mentor and lead a team of machine learning engineers and data scientists, guiding project direction and fostering professional growth. Lead the development of ...

DoorDash
San Francisco, California

We’re looking for a passionate Applied Machine Learning expert to join our team. In this role, you will utilize our robust data and machine learning infrastructure to build new AI solutions to optimize Merchant menus, the most important properties for both Merchant and Consumers. You will be expecte...

Greylock
San Francisco, California

Our ideal candidate will be a self-starter with a strong academic foundation, 5+ years of experience in deep learning and NLP, and recent industry experience with LLM's (prompt engineering, fine tuning, etc. ...

Square
San Francisco, California

The Underwriting systems engineering team is the main interface between the world of ML and product engineering, and as such your work will include everything from backend engineering, developing data pipelines, to creating features, and working with rules engines. Work cross-functionally with produ...

Greylock
San Francisco, California

This will be a hands-on / applied machine learning role with a focus on Generative AI, RAG, and document understanding (Taxonomy, Digitization, Classification, Extraction, Validation, etc. ...